Experiment data investigation and visualization in laboratory

Abstract

To solve a problem in which a software tool usable for assistance of data visualization and analysis normally requires data introduced from different sources and lacks capability to integrate additional information useful for visualization and analysis with such data.SOLUTION: The present disclosure provides a system and method for data analysis of experiment data. The analysis may include reference data that is not directly generated from a current experiment. The reference data may be a value of an experiment parameter that is any one provided by a user, calculated by the system by using input from the user or calculated by the system without using any input from the user. Another example of such reference data may be information on an apparatus such as a calibration method for the apparatus.SELECTED DRAWING: Figure 1

Description

[Background technology]

[0001] [CROSS REFERENCE TO RELATED APPLICATIONS] This application is a continuation of U.S. Provisional Patent Application No. 62 / 186, both filed on June 30, 2015. 928 and 62 / 186,936, under 35 U.S.C. Section 119(e). The contents of each of which are incorporated herein by reference in their entireties. Be absorbed.

[0002] Data visualization and analysis are important tools in life science research. Data visualization is a computer graphics, scientific, and Applications of visualization, both statistical and information visualization. Examples are visualization of HPLC curves, gel electrophoresis Images, DNA and protein sequences, genomes, alignments, phylogenies, macromolecular structures These include endothelial, systems biology, microscopy, and magnetic resonance imaging data. Software tools available to aid in the visualization and analysis of data from different sources Such data usually requires the introduction of additional information that is useful for visualization and analysis. They lack the ability to synthesize information.

[0003] Life science research projects typically involve many stages over a long period of time, each of which The stages may require different equipment and may have different input and output samples. For example, siRNA screening involves siRNA synthesis, purification, validation, quantification, cell-free analysis, and biosynthesis. Any single instrument may be designed to perform a wide variety of such experiments. It is not designed to be a one-size-fits-all solution, but rather to be a multi-modal solution that uses many techniques, many devices, and many platforms. Any system or method for flexibly specifying and automating research projects using In fact, the combination of techniques is nearly exponentially large. Due to the nature of the technique and the myriad of specific parameters that can be varied within each technique, Many consider a generalized experimental platform to be impossible. Despite ambitious demands for flexibility, functional systems are often limited to specific tasks (e.g., specific enzymes). Small, restricted, focused on high-throughput screening of ligands for Focus on automating or electronically representing a well-defined set of experiments is the current practical status quo in the field. This limited approach can be avoided altogether. Thus, the exponential scale generalization problem is "addressed." ,They do not provide the technical basis for building truly flexible and general,experimental systems.

[0004] One reason for this is the lack of existing electronic systems for managing, storing and displaying experimental data. The system is used in a machine-readable form that is amenable to computerized analysis and inference. The advantage of this approach is that it does not specify the experimental protocol to be used. Even when researchers had access to the data, they lacked a thorough understanding of the experiments that generated the raw data. For example, in the Indigo Electronic Laboratory Notebook ("ELN"), experimental protocols are It is just free text. For example, EPAM Life Sciences, Indigo ELN See User Guide version 1.2, Figure 18, bottom right panel. Thus, Indigo The information about the experimental setup in an ELN is not machine parsable, but humans can The experimental protocol information embodied in the Lee Text cannot be programmatically validated. , and cannot be correlated with other information stored in the system. One consequence of this is that in many fields Verify the completeness of the experimental protocol information, including free text, as observed in Another consequence of this is that it is not possible to The inability to link experimental data collected in an efficient and reliable manner It is possible to implement a general framework for linking experiments together that is extensible. To perform. Summary of the Invention

[0005] The present disclosure provides, in some embodiments, a system and method for data analysis of experimental data. The analysis includes reference data not generated directly from the current experiment. The reference data may be provided by the user or may be integrated into the system together with input from the user. calculated by the system or calculated by the system without any input from the user Other examples of such reference data include values ​​of experimental parameters that are either can be information about the instrument, such as how to calibrate the instrument.

[0006] In one embodiment, a system for analyzing data obtained from a laboratory experiment is provided. A program code is provided, the program code comprising a processor, a memory and a program code. The experiment node is configured to store values ​​for experiment parameters for the execution of an experiment. a data module configured to store results obtained from the experiment; an equipment module configured to store information about an equipment on which an experiment was performed; an environment module configured to store an environment state in which the experiment was performed; and a data module. a data visualization module configured to display a visual representation of the results stored in the data table; , and the visual representation further comprises values ​​for the experimental parameters, information about the instrument, and a description of one or more reference data points selected from the group consisting of: do.

[0007] Another embodiment provides a system for analyzing data obtained from a laboratory experiment. The present invention relates to a method and apparatus for implementing a computer-implemented computer-implemented program, the method comprising: Identification of the samples used in the experiment, identification of the equipment used to perform the experiment, and identification of the data generated from the experiment. Identifiers for the datasets generated and environmental conditions for when and where the experiments were performed and an identification of an environmental record that includes the measurement value; and Set, an identifier for the experiment generating the dataset, and the analysis performed on the dataset A data module configured to display a data extract or visualization to represent the identifier. The test procedure includes a list of experiments performed on the instrument, a list of control experiments performed on the instrument, and an equipment module configured to display maintenance records relating to the equipment and the data analyzed; configured to display an analysis summary or diagram representing the set identifier and the results of the analysis The analysis module is now configured to display the environmental conditions of when and where the experiment was run. and an environment module configured in such a manner that the user can The user is presented with a displayed experiment panel and is then asked to investigate information about the experiment. ) The user clicks on the experiment panel identifier of the dataset generated from the experiment. and thereby the identification of the analysis to be performed on the dataset on the Data Panel. The data panel is a data module that displays the You can also select the Data tab to call an analysis module that displays an analysis summary or chart that represents the results of the analysis. Allows the user to click on an identifier for the analysis to be performed on the set, which can then be invoked. and (2) allowing users to click on identifiers of environmental records, thereby You can also call the Environment module, which displays the environment state of the experiment and where it was run. and (3) allowing the user to click on an instrument identifier to run an experiment. This allows the display of a list of control experiments performed on the instrument, as well as the by invoking an equipment module that displays maintenance records relating to equipment associated with the test; Make it possible.

[0008] The present disclosure, in some embodiments, provides a method for designing, coordinating, scheduling, and administering laboratory experiments. Implement an integrated system for logging, editing, executing, analyzing, visualizing, validating, and sharing. Also provided are systems, methods, computer readable media, modules, and means for Such a system would allow for heterogeneous experiments performed on heterogeneous equipment for heterogeneous experiment types. Moreover, information from different entities can be shared, and the Different samples, experiments and instruments are integrated to benefit design, validation and analysis. can be.

[0009] The integration of the system of some embodiments of the present disclosure may be achieved in at least some aspects. For example, the user may input one or more parameters for an experiment. After that, the system validates the parameters and suggests alternative or optimal parameters. Adjust other parameters accordingly, or modify other parameters for which no user input was given. Therefore, the input from the user is not restricted. Rather, the system is designed to provide a life-saving method for performing experiments that lead to high predictability and reproducibility. A complete set of instructions and parameters can be generated. Such instructions are itemized and It can be linearized, parallelized, or otherwise optimized to perform experiments. Provide clear commands.

[0010] Another advantage is that it is possible to identify experiments that generate data, receive the generated data, and / or or in the same interface, facilitating the design of additional experiments after data has been generated. The goal of the integrated system is to enable users to perform analysis using the Although not necessarily visible, the present system in certain embodiments Generate the complete set of parameters.

[0011] The disclosed invention is a free and unstructured encoding of information that is difficult to classify or quantify. In one embodiment, the present technology is different from the conventional technology that uses a bird. For example, a user interface that supports structured input of both experiments and data. Provides support for programming languages ​​within the Compared to the mass free text entry systems that allow is a set of parameters that describe the experiment specification, the actual execution of the experiment, the data generated, and the It allows the analysis of linear sequence data to be correlated. The elements, as well as the entire sequence, are machine readable and amenable to unambiguous computation.

[0012] According to one embodiment of the present technology, the The system ensures this at each stage during the design of the experiment. The assurance is that the description of the experimental protocol is complete, i.e., that all necessary information is provided to carry out the experiment. In another aspect, the assurance means that all information required is included. Protocols are automatically linked to the actual experiment run, the control log, and the output samples. The goal is to generate a log detailing the data generated by the system, and to generate a report that includes the data generated by the system. In some embodiments, a link may be provided to link one experimental protocol to another. Simply copy and paste the original experimental protocol into Instead of subsequently changing the input samples, the user can directly refer to the first experiment. Then the user can decide what they want to change (for example, but not limited to, It is only necessary to specify the different inputs and temperatures. is very compact and can be easily modified without any loss of completeness, accuracy, or repeatability. According to one embodiment of the present technology, the system is configured to ensure that when a user copies an experimental protocol, , new parameters or inputs can be adjusted and validated.

[0013] Another embodiment of the present disclosure provides programmatically reasonable default settings for an experiment. All the user needs to do is specify what is to be different. is used when experiments are not represented in a machine-computable form, e.g. in free text. It is not possible to do this, and the default settings do not include every single parameter that the experiment requires. This greatly improves usage and ease of use by not forcing users to enter data. In yet another embodiment, the experiment is automatically performed by the materials used in the experiment, e.g. For example, this may be combined with logistical information about the shelf life of the storage solution used.

[0014] Another advantage of certain embodiments of the present technology is that the analysis module automatically understands the output of the experiment. Because when you specify an experiment in advance, the system contextually determines the output. Because I know the definition.

[0015] The accompanying drawing figures illustrate, by way of example only, embodiments provided. [Brief description of the drawings]

[0016] [Figure 1] FIG. 1 illustrates a user interface for selecting an experiment type to be run on the system of the present disclosure. [Diagram 2] FIG. 13 shows that after selecting an experiment type, the user is presented with an interface for selecting samples. [Diagram 3] FIG. 13 illustrates an interface through which a user selects samples to be run in an experiment. [Figure 4] FIG. 1 shows how samples for an experiment are selected. [Diagram 5] 1 shows a user interface that allows the user to adjust the experimental parameters. [Figure 6A] FIG. 13 illustrates that certain experimental parameters have been adjusted by the user. [Figure 6B] FIG. 13 illustrates that a warning is given by the system when evaluating the entered values ​​for the parameters. [Figure 7] FIG. 1 illustrates the system confirming that valid experiments are well designed by the user and accepted by the system. [Figure 8] FIG. 2 illustrates an interface of a data module. [Figure 9] FIG. 2 illustrates an interface of an experiment module. [Figure 10] FIG. 2 illustrates the interfaces of the device modules. [Figure 11] FIG. 2 illustrates an example in which multiple objects are interconnected at their interfaces via links, allowing a user to explore related information. [Figure 12A] FIG. 13 illustrates a visualization panel that may be included in an interface to analyze or report modules in various plots. [Figure 12B] FIG. 13 illustrates a visualization panel that may be included in an interface to analyze or report modules in various plots. [Figure 12C] FIG. 13 illustrates a visualization panel that may be included in an interface to analyze or report modules in various plots. [Figure 13] FIG. 1 illustrates how the system integrates different elements of a laboratory research project that may be carried out on the system. [Figure 14] FIG. 1 illustrates some examples of interconnected objects that may be created and utilized in connection with data research and exploration. [Figure 15] FIG. 1 illustrates some examples of interconnected objects that may be created and utilized in connection with data research and exploration. [Figure 16] FIG. 1 illustrates some examples of interconnected objects that may be created and utilized in connection with data research and exploration. [Figure 17] FIG. 1 illustrates some examples of interconnected objects that may be created and utilized in connection with data research and exploration. [Figure 18] FIG. 1 illustrates the overall system design. [Figure 19] FIG. 1 illustrates a system according to one embodiment of the present disclosure. [Figure 20A] FIG. 1 illustrates a system according to some embodiments of the present disclosure. [Figure 20B] FIG. 1 illustrates a system according to some embodiments of the present disclosure. [Figure 20C] FIG. 1 illustrates a system according to some embodiments of the present disclosure. [Figure 20D] FIG. 1 illustrates a system according to some embodiments of the present disclosure. [Figure 20E] FIG. 1 illustrates a system according to some embodiments of the present disclosure. [Figure 20F] FIG. 1 illustrates a system according to some embodiments of the present disclosure. [Figure 20G] FIG. 1 illustrates a system according to some embodiments of the present disclosure.

[0017] Some or all of the figures are schematic representations for illustrative purposes and therefore may not be construed as limiting the scope of the invention. The figures do not necessarily depict the actual relative sizes or locations of the elements. With the express understanding that they are not intended to be used to limit the scope or meaning of the The embodiments are shown for the purpose of illustrating several embodiments. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0018] The present disclosure provides a system and method for integrated laboratory experiment execution and management. The system is connected or interconnected with one or more computers. The laboratory equipment may include a variety of instruments that are connected to the computer. Send commands and receive output, both locally and remotely to each individual device Computers may individually be part of a larger group of computers, e.g. a data center. It can operate as part of a network to facilitate communication between users, devices, and computers. Mathematical Based on the Symbolic Lab Language (SLL), A computer language package has been developed that uses SLL scripts and grammars. With the express understanding that they will not be used to limit the scope or meaning of the claims below. It is presented for the purpose of illustrating conceptual aspects of one or more embodiments. User interface that allows less fluent users to use the system efficiently. Interfaces (e.g., graphical user interfaces, web interfaces, Windows or Mac interface, or mobile interface ) may be created. [User interface for designing and managing experiments]

[0019] 1, 2, 3, 4, 5, 6A, 6B, and 7 show one embodiment of the system of the present disclosure. A user designs laboratory experiments (or simply "experiments") that are performed by an embodiment. FIG. 1 illustrates a computer user interface for performing The process of developing a hypothesis to make a discovery, involving the use of biological or chemical samples or reagents A procedure carried out to examine or establish a fact. An experiment is a single step It can be as brief as a biological or chemical reaction (e.g., 26 It is understood that no experiment is necessary to determine the absorbance at 100 nm. or as complete as is necessary to accept or reject a hypothesis. It should also be understood that the term "technique" as used herein does not refer to a particular A specialized device used to perform a task, especially in the performance or execution of a scientific procedure. For the sake of clarity in this disclosure, the term "technique" refers to an experimental procedure or method. shall be used to mean individual steps that can be combined to perform However, this is purely for the sake of clarity and the term "experimental" as used in this disclosure This does not limit the scope and definition of the term. For example, a technique is also an experiment. As used herein, the term "protocol" refers to a plan for a scientific experiment. Similarly, this term is used for clarity of context and is not intended to be a definition or scope of the term "experiment." For example, the term "experiment" in the context may refer to the protocol for that experiment.

[0020] In FIG. 1, the interface 100 includes a menu area 101, a main panel 102, and and a computer script panel 103, which is sometimes referred to herein as a "note ", "laboratory notebook," or "electronic lab notebook." As used herein The term "script" refers to a program that is pre-compiled into a machine language program or written in a computer programming language or scripting language that can be executed without being The Computer Script Panel refers to the instructions written in a programming language or script. The computer is configured to interactively display and process instructions written in a predefined language, and optionally The display may be configured to display and process text, data, images, and other media. Panels may also be incorporated within other panels. For example, in some embodiments In this regard, the script panel may be used to organize data, experiments, visualizations, and other aspects of the invention disclosed herein. The panels are structured to display the graphical user interface. or as a result of a script command entered in the Scripts panel. Similarly, the modules may also be integrated with other panels, as discussed elsewhere in this disclosure. The menu area can be integrated into the user interface. At any point during the process, the menu contains a list of menu options 104 for the user to select from. The new item "Project" is a form of experiment recorded in a notebook. Allows you to organize your experiences and allows you to create, view, modify, delete, and share projects. Samples allows users to add, modify, annotate, and select samples. The samples can be selected, deleted, or inspected by the user from a remote location. The sample menu also allows the user to view the receipt status of the samples, The menu item "Model" allows in particular to check the quantities and states, etc. A number of physical properties that may be associated with a sample, as well as generalized concepts relating to physical objects. Various conceptual frameworks, ontological entities, which parameterize the conceptual placeholders, Give users access to summaries of controlled terminology, controlled taxonomies, or other knowledge descriptions A "report" is generated by the system during or following an experiment. Displays reports and allows users to generate visualizations, extract or manipulate data, etc. and allows for the inspection of experimental processes and conditions. Another menu item, Data, allows you to choose between raw, processed, structured, or Provides access to the data that has been extracted or that has been displayed in a menu area or The menu options available in this manner are not limited to those illustrated above or in FIG. For example, additional menu choices are "Experiment", "Plot", "Simulation", etc. These terms may include, but are not limited to, "analysis," "searching," and "searching."

[0021] When creating a new project, the main panel 102 displays information relevant to the user. It will display the input and allow the user to make suitable inputs. For example, as shown in FIG. From the multiple commands (105), the user selects "Compile Experiment" t (Edit Experiment)” and in response, the interface displays 106 The following shows a list of the types of experiments that can be performed. "Editing" an experiment means changing the specified parameters (samples, etc.) to check the value of any parameter that is not specified, to derive values ​​for any generating the computer objects necessary to run the experiment, and optionally Carrying out experiments in the laboratory, transporting the results, and / or analyzing the results; This refers to the process of authoring or reviewing a script that defines an experiment. In some embodiments, the term "execute" is used synonymously with "edit" and specifically ,Parameter validation, object generation, and, optionally, running experiments in the lab. Finally, while FIG. 1 illustrates one embodiment, other layouts and multiple sets of A panel may be used. [Experimental format]

[0022] Computer systems and software packages that accompany typical commercial laboratory equipment Unlike a page, the disclosed system and software can be used to Thus, the system allows multiple experiments to be performed independently, sequentially or in parallel. may be any compatible set of experiments, including sets that constitute a sequence of experiments either in parallel. This functionality is reflected in the interface. The disclosed system and software advantageously eliminates the need for physically insignificant or dangerous combinations. For example, creating a solid material and then attempting to manipulate it in a liquid handling device. may be construed to deny implementation of the invention as defined in any of the preceding claims, or to limit the scope or meaning of the following claims. The present disclosure illustrates the functionality of one or more embodiments with the explicit understanding that the disclosure will not be used in conjunction with To that end, a listing of the types of experiments and techniques in this disclosure is provided.

[0023] Thus, in one embodiment, the list of experimental procedures may be of at least one of the following types: At least two of: synthesis, purification, amplification, quantification, and cell culture. In one embodiment, the list includes at least synthesis and purification. and quantification. In one embodiment, the list includes at least purification and cell culture. .

[0024] In some embodiments, the list further includes techniques other than quantification (non-quantification techniques). Non-quantitative techniques include, for example, chromatography, microscopy, electrophoresis, spectroscopy, and In certain instances, the inventory may include at least a nucleic acid or These may include protein synthesis, nucleic acid or protein analysis, and nucleic acid amplification. Techniques can be of several types. For example, high performance liquid chromatography (HPLC) is used for It is both a production and quantification type technique.

[0025] "Synthesis" refers to the production of organic or biological molecules from starting materials without the use of cells. Organic synthesis can be total or semi-synthetic. Total synthesis refers to the synthesis of a simple, commercially available The complete chemical synthesis of complex organic molecules from commercially available or naturally occurring precursors. Total synthesis can be achieved either by linear or convergent methods. In this method, several steps are carried out one after the other until the molecule is completed. The chemical compounds obtained by synthesis are called synthetic intermediates. For more complex molecules, different approaches are preferred. Convergent synthesis involves the individual preparation of several "pieces" (key intermediates). These are then combined to form the desired product. Chemical substances isolated from natural sources (e.g., plant material or bacterial or cell cultures) as These naturally occurring biomolecules are usually large and complex. molecules, which are made up of smaller, cheaper (usually petrochemical) building blocks. This is the opposite of total synthesis, which is done by the stepwise combination of

[0026] In one embodiment, the synthesis is a biological molecule (e.g., a nucleic acid or a peptide) synthesis. Nucleic acid synthesis is the chemical synthesis of relatively short fragments of nucleic acids with defined chemical structures (sequences). In some cases, the process involves the phosphoramidite approach and the synthesis of protected 2'-deoxy Synucleosides (dA, dC, dG, and T), ribonucleosides (A, C, G, and and U), or chemically modified nucleosides, such as LNA or BNA. The synthesis is implemented as a solid-phase synthesis using phosphoramidite building blocks prepared by the method. Peptides are also available that have a carboxyl or C-terminus of one amino acid. It can be synthesized by linking it to the amino group or N-terminus of another amino acid. Due to the possibility of reactive groups, it is usually necessary to protect the peptides. Non-limiting examples of molecular synthesis include, but are not limited to, liquid phase synthesis or solid phase synthesis. Examples include DNA / RNA synthesis, organic synthesis (milligram to gram scale), and Peptide synthesis.

[0027] "Purification" refers to the process of isolating a desired substance (e.g., a cell, a compound, a nucleic acid, or a peptide) from a sample. It refers to a process for increasing the concentration of a substance (molecule) that is usually considered an impurity. Non-limiting examples of purification experiments include genomic DNA preparation, centrifugation, flow cytometry, and the like. Cytometry, fast protein liquid chromatography (FPLC), flash chromatography HPLC (ion exchange), HPLC (reverse phase), RNA extraction, cDNA preparation Protein extraction, solid-phase extraction, thin-layer chromatography (TLC), agarose gel electrophoresis Electrophoresis, capillary electrophoresis, cross-flow filtration (TFF), dialysis (preparation), fluorescence activated cell Cell sorting (FACS), HPLC (normal phase), HPLC (mixture), immunoprecipitation, gas chromatography roughy, gas chromatography-mass spectrometry (GC-MS), liquid-liquid extraction, and supercritical Examples include sequential flow chromatography (SFC).

[0028] As used herein, the term "amplification" refers to increasing the number of copies of a nucleic acid fragment in a sample. The most well-known amplification method is the polymerase chain reaction (PCR). ) method, which is based on quantitative real-time PCR (qPCR) and digital droplet PC Contains R.

[0029] "Quantification" refers to the process of determining the amount of a biological substance, particularly a protein or nucleic acid molecule. Non-limiting examples include total protein, fast protein liquid chromatography, FPLC (FPLC), HPLC (ion exchange), HPLC (reverse phase), thin layer chromatography Fluorescence (TLC), UV / Vis spectroscopy, Western blot, microarray analysis, These include flow cytometry, HPLC (normal phase), and HPLC (preparative).

[0030] "Cell culture" refers to experiments in which cells are grown or in which experiments are performed on cultured cells. and, for example, protein expression, apoptosis analysis, mammalian cell culture, gene transfer, bacterial These include cell culture, yeast cell culture, colony picking, and electroporation.

[0031] "Non-quantitative analysis" refers to analysis that uses specific characteristics other than mere quantification (e.g., molecular weight, molecular identifiers). , sequence, size, purity, pH, kinetics, charge, melting point, glycosylation status) Non-quantitative analysis refers to any experiment that determines whether a Balance readings, epifluorescence microscopy, fast protein liquid chromatography (FPL C) Flash chromatography, fluorescence kinetics, fluorescence polarization, fluorescence spectroscopy, and fluorescence thermodynamics , HPLC (ion exchange), HPLC (reverse phase), optical microscopy, MALDI mass spectrometry, pH reading, polyacrylamide gel electrophoresis (PAGE), thermometer reading, thin layer TLC, UV / Visible (Vis) kinetics, UV / Vis spectroscopy, UV / Vis thermodynamics, Western blot, volume check, agarose gel electrophoresis, raw atomic absorption spectroscopy, atomic emission spectroscopy, atomic force microscopy, capillary electrophoresis, circular polarized light Chromatography (CD), confocal microscopy, dialysis (equilibration), differential scanning calorimetry (DSC), DNA Sequencing (next generation), DNA sequencing (Sanger), Dynamic Light Scattering (DLS), Electron Microscopy, Electrospray ionization (ESI) mass spectrometry, enzyme-linked immunosorbent assay (ELISA), H PLC (normal phase), HPLC (mixture), fluorescence in situ hybridization (FISH), gas chromatography Chromatography, gas chromatography-mass spectrometry (GC-MS), inductively coupled plasma mass spectrometry (ICP-MS), infrared spectroscopy, isothermal titration calorimetry (ITC), liquid chromatography LC-MS, melting point determination, microarray analysis, NMR (2D / structural), NMR (carbon), NMR (proton), patch clamp recording, photostimulated luminescence (P SL), supercritical fluid chromatography (SFC), refractometry, scanning tunneling Microscopy, solubility test, surface plasmon resonance (SPR), tandem mass spectrometry (MS- MS), total internal reflection fluorescence (TIRF) microscopy, and X-ray crystallography. do.

[0032] In some embodiments, the listing further includes one or more of the following experiments: Reeve, buffer formulation, liquid handling, freeze drying, rotary evaporation, speed vac concentration, vacuum filtration filtration, virus preparation, Arabidopsis studies, bioreactors, bomb calorimetry, C. elegans research, crystallization, Drosophila research, flow chemistry, plasmid construction, sonication , tissue homogenization, ultracentrifugation, microwave reactions, and molecular cloning. [Convert and display scripts]

[0033] In the interface 100, the user may inform the system of the desired selection, for example in the main area 102. As shown in FIG. 2, the command may be "West A Western Blot experiment should be performed. The instructions are translated into computer code to instruct the corresponding equipment to carry out the experiment. In some embodiments, the computer code may be in the form of a scripting language. In one embodiment, the scripting language is Symbolic Lab Language (S LL).

[0034] SLL is based on the Mathematica® language. User-friendly grammar and comprehensiveness provided by ematica® In addition to the standard data manipulation and visualization capabilities, SLL also provides specific As used herein, the term "object" includes descriptions of functions, objects, and findings that are specifically designed. Thus, an "object" without further qualifier means a data structure, and / or functionality. And importantly, modules provide efficient equipment management and It is designed to interface with many laboratory instruments to enable communication and data transfer. It is being built.

[0035] SLL can be supported by a variety of databases with varying performance tradeoffs. As used herein, the term "database" refers to a computer-maintained A structured set of data, especially one that can be accessed in a variety of ways. Non-limiting examples of data types include relational, graph, probabilistic, XML, SQL, Non-limiting examples of databases include P ostgreSQL, MySQL, Oracle Relational DBMS, M These include OngoDB, DB2, and Cassandra.

[0036] The SLL provides an objective system for querying, manipulating, and displaying experimental results. The data points included in the plot (e.g., chromatograms or spectra), images ( gels, blots, and microscope slides), and metadata (e.g., experimental the date on which the experiment was performed, the reagents used in the course of the experiment, and the equipment utilized to perform the experiment The results of each experiment, including the results of the experiment, are represented as objects, which are then processed and In one embodiment, this is the case for such an association. A pointer or "key" that can be used to access more conceptually separate information This is achieved by means of a "key". One object may be related to several different experiments. For example, if an instrument object is associated with a precise experimental procedure, sample type, etc. This is particularly powerful when linking all experiments that utilize the instrument.

[0037] This setup allows multiple nodes to be analyzed without losing quantitative precision and any relevant details. Enabling scientists to easily and compactly share data across projects and teams to.

[0038] Furthermore, the computer system of the data objects for each SLL Preparation: Write scripts that process the inputs and process them in an algorithmic fashion. By giving people the ability to abstractly manipulate large sets of experimental data, This makes it possible.

[0039] SLL and some of the inventive concepts of this disclosure exemplified by implementations of SLL To make this more clear, the following is a list of SSL objects, functions and non-limiting examples of their use: This is a typical example.

[0040] Example of a data object: data[index, <type>], e.g. data[ 44,NMR] may refer to the 44th nuclear magnetic resonance (NMR) experiment performed in the laboratory, d ata[1023, MALDI] is the 1023rd matrix-assisted laser desorption Refers to the combination of results from MALDI experiments. The method is not important, and no chronological ordering or any particular symbolic identifier is required. For example, a user-defined string can be used to ensure that the system has a high degree of confidence that it represents the intended object. It may be used to identify an object as long as it is sufficient to reliably identify it. obtain.

[0041] Example function: info[] - Call info on a data object, e.g. info[ data[44,NMR]] connects to the database and then associates it with the experiment. In some embodiments, the info[] object returns a list of all the data that has been Further calls will be made to the ) info will automatically reference the locally cached copy. The database is configured to cache that data. inform[] - a list of all data associated with the experiment in the form of substitution rules. The call to inform in checks whether the data has already been inserted into the database. If so, it checks to see if the previously inserted data[] object is If not, insert the data into the database and It will return a new data[] pointer to the object.

[0042] SLL also includes the ability to track and query the complete history of a laboratory sample. Examples of information tracked include information about the source material, the process involved in its creation, Its current characteristics, such as preoperative information, the experiments in which it is used, quality assurance (Q A) Information about the substance, its several properties, such as volume, concentration, and pH, chemical composition, etc. which information about its inherent properties and physical The location can be mentioned.

[0043] Adding an Object Example The object represents a physical sample. <type>] For example, sample["Nearest Neighbor Strand 4 Strand 4) "DNA" is a set of DNA sequences that contain information about the materials, dates, and events involved in its creation. The experimental results from the experiment, its sample attributes such as volume, pH, concentration, etc., as well as its Information about the sample, including its physical location in the laboratory (where it is stored) Encapsulate. group["group name"], for example, group["Nearest Neighb or Strands"] are the ones that the experimenter wants to manipulate in large quantities, A group may refer to a collection of samples of any size. The sample may be a member of multiple groups.

[0044] Protocol objects are created following the execution of an experimental function. For example, the command E xperimentHPLC[sample["Crude Nearest Neig hbor Sequence 5 (5th most recent unanalyzed sequence)"], Method → ​​I onExchange,FlowRate→3 Milli Liter / Minute ], the protocol object protocol[12345,HPLC] is executed. The protocol object will be used by the system and will be generated every 3 minutes. A preparative ion-exchange HPLC run at a flow rate of 100 uL was used to determine the most recent sequence that was not analyzed. The new physical sample (and corresponding sample object) obtained from the refinement of 5 In this way, the experiment function allows you to create and interact with experiments from within the lab notebook. It is used to direct physical activity in a room. In a preferred embodiment, this includes Protocol objects are involved, but other object configurations may be used. In a preferred embodiment, the protocol object is returned to the user.

[0045] In a preferred embodiment, a protocol object representing an experiment is stored in a real laboratory. The commands and specific actions are placed in a queue to be processed. The execution of any experiment function from within the program transfers the samples and instructions involved in that process to the process. The process queue starts by adding the process to the physical skew in the lab. A queue of experiments waiting to be executed. In some embodiments, managing the process queue involves In other embodiments, the process queue is run by a computer. managed by algorithms or a mix of human and algorithmic decision making After an experiment is removed from the queue and run, the user who originally started the experiment will You will be notified that the experiment has been completed and the results of the experiment (samples and / or In a preferred embodiment, the user will receive samples and and / or data and allow the user to access relevant information about the results. Receives a computer object that enables

[0046] In addition, the protocol object is removed from the queue and sent to the orchestration module. When processed by the tool, the specified experiment (usually known in the art as an experimental protocol) (hence the name "protocol object") to The orchestration module generates the actual instructions on which the experiment should be executed. It can be placed in the laboratory and can be remote as long as it is capable of communicating with the laboratory where the experiment is to be performed. The human operator performs a given experiment in the laboratory. When the relevant aspects of the generated instructions are Dynamic and interactive checks on your smartphone or other remote devices that can share information. When the operator finishes the process, these checks are The list marks the completion of each step and includes the file name from the instrument, standard findings, or predictions. A field for entering information, such as further details on what to do if you run into unexpected difficulties. The generated instructions will be displayed along with the experimental parameters, physical sample inputs, and environmental sensors. In part because of programmatic coupling with the database and other contextual information, The embodiment also tracks source materials used during the course of an experiment and stores that information in output samples and Barcode or radio frequency identifier tags for automatic linking to any result data It also supports integration with specific equipment programs and physical tracking devices, such as Moreover, the generated instructions themselves can be dynamically changed in response to information received from the laboratory. Those skilled in the art will appreciate that the specific sequence assigned to a human by the orchestration module is Steps can also be assigned to robotic systems, either alone or in conjunction with humans. It will be readily understood that such modifications are also within the scope of the appended claims. cormorant.

[0047] Once received, the command at the user interface 100 is processed by the computer. Once converted to script, the script can be displayed in the script panel 103. Such a display serves several purposes. First, the user can display the script in the graphic interface on the left. Second, the script language can be used to verify the command by comparing it with the user's command via the script interface. A user who is not familiar with a specific language, e.g. SLL, can navigate through a graphical user interface. By focusing on dynamically generated scripts based on user input in Third, the user can become familiar with the language. You can enter scripts directly into the script file or modify existing scripts. Writing provides better flexibility and more control over scripts. Providing direct access to the user may give the user additional power. In a preferred embodiment, the script panel is similar to that used in e.g. Mathematica. scripts are part of an interpretive development environment that can be used to It is written in an interpreted computer language, such as the Olfram language. supports other interpreted and compiled languages, e.g. SciPy or NumPy, It also supports compiled and interpreted development environments.

[0048] In some embodiments, the user enters script commands directly into the script panel. When an addition or change is made to an existing one, the addition or change may be reflected in the panel 102. For example, if a user were to run the script shown in panel 103 as "experiment[We sternBlot(Western Blot)]" to "experiment[Tran If you change it to “S-transfection”, the user will be asked to provide the protein sample and Instead of prompting the user to select a DNA sample and an antibody sample, the interface This will facilitate identification of the patient and cell sample. [Sample Selection]

[0049] Once the experiment type is selected in 106, the system will determine the type of samples required for the experiment. The system will determine the group and prompt the user to select the appropriate sample. For example, in the example in Figure 2 In the, user clicks on "Western Blot" The system then performs the following: such experiments require protein samples and antibody samples. Therefore, two input fields, 20 1 and 202. In some embodiments, the system The sample type and other parameters will only be determined when they are seen.

[0050] Samples can be sent to a facility, created from scratch, or integrated into the overall system. A sample can be identified from a computerized data source as an already existing sample. When creating a sample (or entering a new sample into a data source), the user The various options to be annotated, i.e., concentration, volume, purity, date of production, etc. Specify the values ​​of several properties and / or the name of the laboratory or technician who prepared the sample. In a preferred embodiment, the options include, but are not limited to: The system may then proceed to request annotation of certain characteristics, e.g. It is constructed to ensure that information essential to the execution of an experiment is input.

[0051] Depending on the type of sample or experiment, several specific characteristics of the sample influence the design of the experiment. For example, the pH and concentration of a protein sample may be required for an HPLC experiment. The pH and concentration are not provided by the user and therefore may be required in the system. The system will have to deal with data that does not exist. For example, the system The pH and concentration of the solution are then determined and, if necessary, the steps of adjusting them to the optimum values ​​are then added. Prior to such a decision, or in the absence of such a decision, The system may use a pre-determined default value. The system may also The user may be prompted to enter a pull characteristic value.

[0052] In some embodiments, the system detects important parameters (e.g., pH, concentration, volume ) to determine whether such information was provided by the user in the sample. This is to prepare a step for when the information provided by the user is not accurate or This is useful if information is changed, for example during transport. The system ensures internal consistency. Cross-checks related to multiple parameters or dependent on multiple characteristics to verify It is also possible to carry out

[0053] When selecting samples for an experiment, the user selects Menu 3 as shown in FIG. Highlight the desired sample from 01 and drag it to the appropriate area (201 or 202) As explained above, such a selection of samples can be done by simply clicking and dropping the This will result in the generation of a corresponding computer script. It will be displayed at 103.

[0054] In some embodiments, not illustrated in the figures, the user first selects a sample. In this scenario, the user may choose to select the experiment type. When you indicate the experiment type, the system will populate the list of experiment types according to the sample type. For example, Western blots can be used to filter DNA samples. The user will also be able to scroll without the aid of graphic aids. You can enter the script directly. [Experimental parameter adjustment]

[0055] Once the experiment type and sample have been specified, the system then prompts the user to An interface for setting parameters will be shown (e.g., panel 50 of FIG. 5). 1). The exact experimental parameters shown for user input and / or adjustment are Not only does it depend on the experiment type, but it can also be influenced by the sample selected. Please note that.

[0056] When the user indicates which experimental parameters to input or adjust, the system also may determine a subset of parameters that are preferred, desired, or required. For example, for a Western Blot experiment, the system uses a user-defined staining time. and cleaning time can be determined to be better than other parameters. The two items may be highlighted to attract the user's attention.

[0057] In some embodiments, the system further includes a user-defined parameter in addition to the experimental parameters. In one embodiment, the desired outcome comprises one or more desired experimental outcomes to be determined. The product generated from the experiment is delivered at the desired concentration, purity, and weight (or copy number). Once the interface receives input from the user regarding such a desired outcome, Once the user has input the desired results, the system will then calculate the appropriate experimental parameters to achieve the desired outcome. The desired experimental result can also be a parameter. [Parameter Resolution]

[0058] The disclosed system may, in some scenarios, be used to measure the time course of an experiment when all parameters are determined. are set aside for future reference before the experiment is actually performed (alternatively called "solved"). There are at least three benefits to such an effort: First, once an experiment has been designed with the solved parameters, The user can be assured that the experiment will run as intended, without the need for further input, adjustments, or corrections. (with certain significant limitations, such as sample degradation during transport) Second, parameter resolution does not allow you to choose any parameters for the experiment run. This also removes the ambiguity of the hypothesis, and thus eliminates a major source of experimental inconsistency, so the experimental results are Third, future experiments will be able to replicate the samples and underlying parameters. Either the experimenter or the researcher may choose to use the results of the experiment, without losing any contextual knowledge of the experiment. Therefore, data and samples generated in the distant past can be used to compare data and samples generated yesterday. As well as samples, they can be a useful basis for further experimental inquiries. In other words, as further exemplified below, the present technology is In addition, this programming of experimental parameters allows for high predictability and reproducibility. Programmatic identification and resolution is only possible in an integrated electronic system. It is worth noting that without a machine-readable definition of a given experiment, it is difficult to understand what is being required. It would be impossible for a computer to understand this. Therefore, the request must be well-formed and sufficient. It will not be possible for the present study to be of any assistance in determining whether

[0059] Irreproducibility is a major concern in the scientific community, especially those related to the life sciences. One type of irreproducibility has long plagued researchers. It comes from the efforts of scientists to try to reproduce the results of a study. In an effort to identify the main cause of the problem, an experiment was carried out (Vasile vsky et al., Peer J. 2013 Sept. 5, 1:e148). Some of the inconsistencies This is due to the lack of “identifiability” of the reagents, tools, and model systems used. It was hypothesized that 54% of these resources were uniquely identifiable. Instead, it was found to make it difficult for an equal to reproduce the exact test conditions.

[0060] Another type of irreproducibility is when someone, either the same person or a different person, in the same laboratory or organization, This occurs when an experiment is repeated that was done earlier by a More researchers fail when trying to replicate another scientist's experiment, and more than half "Failed to replicate their own experiment" (Nature 533, 452 -454 (May 26, 2016). At least one such highly unreproducible The reason is ambiguity in the setting and / or recording of experimental parameters or conditions. In some embodiments of the presently disclosed technology, all experimental parameters The program or conditions (sometimes called "options") are resolved before the experiment is run. The process may be called "option resolution" or "parameter resolution."

[0061] One aspect of parameter resolution is that parameter identifiers, i.e. Another aspect concerns what parameters and conditions need to be determined. Decisions regarding these parameters and conditions, including whether the decision may obtain input from the user In yet another aspect, after receiving the user input, the system Inspect the input and, if necessary, provide recommendations, warnings, or automatic adjustments. Each is described in further detail below.

[0062] The parameters and conditions determined for an experiment before the experiment is carried out are those that have been used in similar experiments in the past. These are usually broader than those used when performing a HPLC system. In a traditional HPLC experiment, before the start of the HPLC experiment, the technician must decide which column to use. Alternatively, the concentration and volume of the sample, buffer, and flow rate may be determined. Other parameters or conditions remain largely undetermined or the experiment is physically It is part of the unrecorded, tacit knowledge of the person who does it. Often people do not know what will be important or influential, so the parameters are recorded. It is important in scientific inquiry to ensure that records are selective and To rely on chance runs a very high risk of omitting valuable insights.

[0063] One type of parameter that is not typically specified in a traditional experiment is the preparation or calibration of the instrument. For example, in the HPLC example, additional flush runs are inserted between samples. The parameter "flush frequency", which specifies how often the flushing will occur, depends on the practice of the particular laboratory. or by the habit or training of the engineer. Moreover, this important information Even when they have the potential to have a major impact, they are often not written down or For example, internal experiments are not recorded in a manner that is linked to the results data. A particular flash frequency introduces enough variability within a single experiment to render it useless. However, this essential part of the information is still not recorded in conventional systems. Another such example is to check whether the standard was executed after each additional flush run. A further example is the "post-flash standard" which determines whether The photodiode amplifier gain, which may have a large effect on the experimental findings, Regardless, these are parameters that are usually set when the device is first installed and then forgotten. In one embodiment of the present disclosure, however, during the design step of the experiment, The parameters of such equipment preparation or calibration must be specified and the values ​​determined. It needs to be.

[0064] Another type of parameter that is not typically determined in conventional experiments is post-experiment care. One such example is the shutdown method, or cleanup procedure for HPLC experiments. In one embodiment of the present disclosure, during the experimental design step, such The post-experiment care parameters of the equipment need to be identified and the values ​​determined. be.

[0065] Yet another set of parameters not typically determined in conventional experiments is the These are parameters relating to the operations or analyses that can be performed. The choice of which fraction to use can depend on the particular output from the experiment. For example, during an HPLC experiment, The acquisition parameters (e.g., start time, end time, acquisition mode, maximum acquisition volume) are determined. However, in one embodiment of the present disclosure, Thus, the parameters can be determined prior to loading of the sample. For example, the user can load a standard (e.g. For example, you will be prompted to enter a threshold value (peak start threshold) that defines the signal threshold for detecting peaks. which can then be used to determine fraction collection parameters.

[0066] Users may be unfamiliar with many of the parameters that are set for the system to resolve. Therefore, in some embodiments, The disclosed system provides a user interface to the user by including or indicating recommended values ​​for the parameters. In one embodiment, the recommended values ​​for the parameters are For example, for analytical HPLC, the system defaults to The system is prepared by setting the injection volume to 1 nmol in the absence of explicit user instructions. For the HPLC system, the default injection volume is 50 nanomoles. Depending on the user's choice of reversed-phase or ion-exchange HPLC, the system The default temperature parameter is dynamically set to 45°C or 25°C. The same goes for other parameters. The temperature value selected by the system can be overridden by the user. The system will either not be able to resolve it itself or the user will have to provide the system's own resolution value. If you want to override any of the parameters, you must specify Therefore, very compact scripts are possible. For example, in SLL The HPLC experiment function has 43 parameters: notification, acceptance, selection, scale. ,Fraction collection,Injection volume,Flush frequency,Standard after flush,Injection volume,Column , Instrument, Type, Buffer A, Buffer B, Buffer C, Batch Standard Injection Volume, Batch Standard Subsamples, batch standards, flush methods, shutdown methods, gradient standards, graphs Injection volume of standard agent, temperature, flow rate, detection wavelength, gradient B, gradient C, gradient gradient start, gradient end, gradient duration, equilibration time, flush time, Gradient method, fraction collection start time, fraction collection end time, fraction Acquisition mode, Maximum fraction volume, Absolute threshold, Peak gradient, Peak gradient duration, Maximum collection period, peak end threshold, and fraction collection method, all of which are system dependent. Therefore, in the preferred embodiment, any settings recommended for the system Users who do not wish to override the setting can simply type: Experiment HPLC["Sample 1"] Not the rather unwieldy and intimidating one below. ExperimentHPLC["Sample 1", Inform→User V alue, Accept→User Value, Options→User Va lue, Scale→User Value, CollectFractions→ User Value, InjectionVolume→User Value, FlushFrequency→User Value,StandardAfterF lush→User Value,InjectionAmount→User Val ue,Column→User Value,Instrument→User Val ue,Type→User Value,BufferA→User Value,Bu fferB→User Value,BufferC→User Value,Batc hStandardInjectionVolume→User Value,Batc hStandardSample→User Value,BatchStandard Method→User Value,FlushMethod→User Value ,ShutdownMethod→User Value,GradientStand ard→User Value,GradientStandardInjection Volume→User Value,Temperature→User Value ,FlowRate→User Value,DetectionWavelength →User Value,GradientB→User Value,Gradien tC→User Value,GradientStart→User Value,G radientEnd→User Value,GradientDuration→U ser Value,EquilibrationTime→User Value,F lushTime→User Value,GradientMethod→User Value,FractionCollectionStartTime→User V alue,FractionCollectionEndTime→User Value e,FractionCollectionMode→User Value,MaxF ractionVolume→User Value,AbsoluteThresho ld→User Value,PeakSlope→User Value,PeakS lopeDuration→User Value,MaxCollectionPer iod→User Value,PeakEndThreshold→User Val ue, and FractionCollectionMethod → ​​User Value e] Here, "User Value" is the parameter value that the user specifies. What is important is whether the parameters are determined by the system. All parameter values, whether determined by the user or not, are saved for future reference. This is because the user can simply copy the saved parameter values. This means that it will be easy for users to run the exact same experiment again in the future. This can be done automatically by the system or manually by the user. In order to make the script easier to read, but more computationally complete, all the parameters of the experiment are The ability to flexibly specify meters represents a powerful advancement in the art.

[0067] In another embodiment, the recommended value for a parameter may be dependent on another parameter. For example, in one embodiment, once the system has resolved the sample type, For samples determined to be DNA, the system can determine the appropriate detection wavelength. The system suggests that the detection wavelength parameter be set to 260 nm, and the protein For samples determined to be of quality, the system suggests a detection wavelength of 280 nm. .

[0068] In another embodiment, the recommended values ​​for the parameters are not fixed values, but rather are determined by different implementations. A mathematical formula or function that takes input values ​​from another experiment or from another part of the same experiment. In some embodiments, the system is configured to monitor the execution of the experiment. The information collected during the experiment may be used to determine experimental parameters in another experiment or in another part of the experiment. Note that the above information may be used to aid in the determination or adjustment of the

[0069] In one scenario, one or more experimental parameters are determined or adjusted. The information provided may be historical information of the sample, e.g., from prior / upstream experiments. For example, The sample is a cell sample, and the system is adapted to measure the rate of growth of cell types in the sample. When the data is available, then the historical growth rate information can be used to determine whether the cells are growing at a suitable rate. The experimental parameters can be used to adjust the experimental parameters to ensure that

[0070] In another scenario, the method may be used to determine or adjust one or more experimental parameters. The information stored is the history of the device. The device may be periodically calibrated. The results of the calibration are , can be used to guide adjustment of experimental parameters. The results can also be used to adjust and optimize parameters.

[0071] The recommended values ​​for the parameters are, in one embodiment, based on further user input. It can be used to automatically set these parameters if they are not present. The values ​​that are automatically added are illustrated in Figure 5. However, the system imposes certain restrictions. Allows the user to adjust any of the parameters as desired, even if In FIG. 6A, for example, the user may select , Sample Volume, Separation Time The values ​​for Time, and Separation Voltage are When these values ​​are received, in one embodiment, the system The system evaluates the reliability of these values. Only the set is presented to the user for consideration.

[0072] Assuming that some of the parameters are dependent on others, then depending on the embodiment, In such cases, the system checks the reliability of the values ​​in an order that respects such dependencies. For example, in relation to the three parameters adjusted in FIG. 6A, the system first Volume of the cell, antibody volume, luminal volume The values ​​for Peroxide Volume and Peroxide Volume were , check whether it is within the optimal, recommended, or acceptable range. Towards this goal, the system determines the recommended values ​​for the parameters. The optimal, recommended, and acceptable ranges for Note that it may be possible to

[0073] Furthermore, the resolution of some parameters may itself involve other parameters that need to be resolved. The various parameters can be solved based on formulas or functions, and therefore Thus, a complete solution may depend on the resolution of a complex series of interrelated functions. In some cases, the logic for this is not necessarily explicitly programmed into the system. There is no need, rather the solution is the solution of recursive function calls in computer science. It is important to note that this is naturally handled by a sequential resolution of options, similar to It is essential.

[0074] The system then calculates the separation time, separation voltage, stacking time, and me), and stacking voltage, Regarding their suitability for this particular experiment, they have already been evaluated at a previous stage. a volume of sample, an antibody volume, a lumen volume, and a peroxide volume, In the example shown in FIG. 6B, the system evaluates the separation voltage provided by the user. It determines that the pressure is too high and therefore displays a warning on the right hand panel.

[0075] According to certain embodiments of the present disclosure, a user may "Execute Experiment" button on the interface After you have completed the experiment design, you will need to click No further input is required. In one embodiment, the input is In one embodiment, the input refers to information regarding the selection of a reagent. In one embodiment, the input includes information regarding adjustment, preparation, configuration, or calibration of the device. In one embodiment, the input includes information regarding the collection of output samples from an experiment. In one embodiment, the input is related to further processing of output samples from an experiment. In one embodiment, the input refers to information about setting environmental parameters for an experiment. In one embodiment, the input refers to information related to the storage or display of experimental results. This refers to information that [Sample receiving and loading]

[0076] The presently disclosed system may enable a computationally complete description of the experiment, so that the experiment , may be performed remotely, either by a machine or a combination of machines and humans, and thus A version of the lab-in-the-cloud concept is being implemented. Therefore, in addition to operation via a computer interface, some In an embodiment, the user can determine where the equipment in the system is located without performing any other physical action. It is only necessary to send the sample to a location (i.e., a laboratory).

[0077] When a sample is entered into the system, information about the sample is sent either before or after the sample. Usually, however, at least each sample is already pre-processed before it is received at the laboratory. For example, each sample has a name or identification number and a preferred or sample type (e.g., DNA sample, protein sample, cell line) In some cases, additional information such as concentration, pH, preparation data, molecular weight, etc. is also entered into the system.

[0078] Once the samples are received at the laboratory, they are placed in storage. Before being delivered or loaded into the instrument, the samples may be inspected for concentration, temperature, volume, weight, and and / or pH measurement. In case of discrepancies with the information provided, adjustments will be made regarding the quality of the sample or the stored characteristics. This may be done or a flag may be raised.

[0079] In some embodiments, experimental parameters for the experiment are determined based on such measurements. In one scenario, the measured results are adjusted based on the user interface. This may be due to, for example, deterioration of the sample during transport or This can be caused by loss of humidity. In another scenario, certain parameters are changed by the user. If not set, the system may use default values ​​from the design of the experiment. [Compound Experiments]

[0080] The capabilities of the currently disclosed laboratory systems, both simple and complex, This is reflected not only in the ability to automate a wide variety of experiments, but also in the ability to design and The emphasis is also on the ability to design and carry out a compound experiment. An experiment that contains a set of experiments, where the output of one of the component experiments is the input sample for the other component experiments. In addition, the two component experiments are performed in a variety of ways, such as molecular synthesis, purification, amplification, quantification, cell culture, and In some embodiments, the compound experiments include at least In some embodiments, the system can be configured to: Compound experiments can be supported that involve many different experiments, depending on the available resources. One part of a compound experiment is dependent on the output or results of another part. Some parts of compound testing may proceed sequentially or in parallel with one another. The execution of one part of a compound experiment may be carried out by first considering the results of another part of the compound experiment, It is up to the user to tailor the compound experiment as desired. The compound experiment is run before the run begins. It is not necessary for the test to be fully specified. For example, users may add additional component experiments over time. In fact, analytical chemistry, cell biology, and and / or molecular biology techniques detailed in any life science publication. The overall experiment can be replicated in specific embodiments.

[0081] One example of a compound experiment involves nucleic acid synthesis (synthesis), followed by nucleic acid purification (purification), nucleic acid This is followed by quantification, then amplification, and then sequencing. In another example, compound testing involves protein expression (cell culture), followed by This is followed by protein purification (purification), and ELISA (quantification).

[0082] Once one component experiment is completed in a compound experiment, the system will generate the appropriate output sample. Samples are collected from the component experiments, optionally followed by suitable sample analysis. For the example nucleotides, concentrations and volumes can be confirmed. If necessary, concentrations, dilutions, pH adjustments, etc. may be performed. This output sample is then fed to the instrument for the next component experiment. The experimental parameters for the next component experiment are also transferred to the sample analysis and follow-up adjustment. The metric can be adjusted on the fly according to

[0083] A compound experiment is a compound that branches off from or is derived from a basic compound experiment. The branching target may further include one or more component experiments. The output samples and / or data or inputs to the third component experiment along with the second component experiment Forming forces, generating samples or data. In contrast, component experiments at the branch end, Share input samples or data with the second component experiment, which were generated from the third component experiment The data collected for each component experiment is then automatically calculated or based on user input. Based on either the results, the experimental parameters of any other component experiments can be adjusted. do.

[0084] Parameter solutions for designing compound experiments take into account the relationships between individual experiments within a compound. See the following example of a compound experiment that includes seven techniques. Phase I: 1) Experiment DNA Synthesis ⇒ Generate DNA samples 2) Experiment HPLC (ion exchange) ⇒ The sample generated in (1) is purified. Manufacture 3) AnalyzePeaks ⇒ Analyze the peaks generated in (2) and Select fraction samples based on Phase II: Now, take the fraction samples selected in (3) and perform the following four experiments in parallel: , or in any order desired by the user. teeth: 4)Experiment HPLC (Analysis) 5) Experiment PAGE 6) Experiment Mass Spectrometry 7) Experiment Absorbance Quantification Phase III: Any one or more analyses may be performed in any order as desired. 8) AnalyzePeaks 9) Plot PAGE 10) Plot Mass Spectrometry 11)AnalyzeAbsorbanceQuantification

[0085] In this example, specific considerations regarding parameter resolution are addressed by the Expert The HPLC experiment was performed in step (2) Many parameters can be inherited. Therefore, once a parameter is ), less input is required from the user for step (4). Advantageously, this also means that many parameter values ​​are explicitly considered. (1) and (4), which may occur in manual configurations that are not considered or recorded. This reduces the opportunity for error caused by inadvertent changing of parameter values ​​between Then, during the processing or analysis of the above steps, one or more of the following experiments are performed on the output sample: It can be carried out. 12)ExperimentAbsorbanceThermodynamics 13)ExperimentFluorescenceKinetics 14) Experiment Transfection

[0086] The above compound experiments are not pre-set by experts, but can be selected by the user. Note that you can change it in a way, or do something else entirely. Any physically permissible combination can be used, e.g., in a high-throughput screening system. This difference in functionality can be implemented in the invention of this disclosure. In other words, the flexibility of the embodiments of the present disclosure is similar to that of a general purpose computer. Flexibility and generalizability allow functionality that was not possible before. As another example, from the methods section of a paper published in Nature Biotechnology The strain was E. coli K-12 BW25113 (genotype: F-, Δ(a raD-araB)567,ΔlacZ4787(::rrnB-3),λ-,rph- 1,Δ(rhaD-rhaB)568,hsdR514) was used to compare all 22 conditions. We generated a proteome map that includes the rimL, rimJ, or rimI genes. Mutant strains with deletions were taken from the KEIO collection. The accuracy of the deletions was confirmed by Furthermore, the glucose-related proteome and LB status were also In addition, the strains MG1655 (genotype: F-, λ-, rph-1) and NCM3722 (genetic "The genotype is determined by the genotype (F+) of the chromosome," Alexander Schmidt et al., The Quantitative and condition-dependent Es cherichia coli proteome,Nature Biotechno logy 34, 104-110 (December 7, 2015). This is the first time that SLL has It can be expressed as follows: Strains baseLine=model["BW25113",Cells] ; rimLLine=model["BW25113ΔrimL",Cells]; rimJLine=model["BW25113ΔrimJ",Cells]; rimILine=model["BW25113ΔrimI",Cells]; altCellLines={model["MG1655",Cells],mode l["NCM3722",Cells]}; Primers rimLFowardPrimer=model["rimLFoward",Olig omer (oligomer)]; rimLReversePrimer=model["rimLReverse",Ol igomer]; rimLBeacon=model["rimLBeacon",Oligomer]; rimJFowardPrimer=model["rimJFoward",Olig omer]; rimJReversePrimer=model["rimJReverse",Ol igomer]; rimJBeacon=model["rimJBeacon",Oligomer]; rimIFowardPrimer=model["rimIFoward",Olig omer]; rimIReversePrimer=model["rimIReverse",Ol igomer]; rimIBeacon=model["rimIBeacon",Oligomer]; [experiment] ExperimentcDNAPrep[{rimLLine,rimJPrimer Set,rimIPrimerSet},PBSSample→model["PBS", StockSolution],LysisSolutionSample→model ["ABIcDNAPrepLysis",Chemical],MediaVo lume→150 MicroLiter, WashVolume →100 MicroLiter, Annealing Temperature→45 Celsius(℃)] protocol[123123,cDNAPrep] lysisSamples=SamplesOut / . Info[cellPrep ] {sample[12451,Lysate(Lysate)],sample[124 52,Lysate],sample[12453,Lysate]} ExperimentqPCR[lysisSamples,ForwardPrime rs→{rimLFowardPrimer,rimJFowardPrimer,ri mIFowardPrimer},ReversePrimers→{rimLReve rsePrimer,rimJReversePrimer,rimIReverseP rimer},Beacons→{rimLBeacon,rimJBeacon,ri mBeacon},TemplateVolume→2 MicroLiter, Fo rwardConcentration→0.5 Micro Molar ), Reverse Concentration → 0.5 Micro Molar, Beacon Concentration → 250 Nano Molar ,DenaturationTemperature→95 Celsius,Dena turationTime→15 Second(seconds), AnnealingTempe rature→60 Celsius,AnnealingTime→30 Secon d,NumberOfCycles→50] protocol[123141,qPCR] qPCRData=Data / .Info[protocol[123141,qPC R]]] {data[124584,qPCR],data[124608,qPCR],da ta[124602,qPCR]} PlotObject[qPCRData].

[0087] The invention of this disclosure was not designed to specifically carry out the experiments in this specification. Rather, the flexibility of the system allows for the implementation of This is highlighted by its ability to reproduce any arbitrary experiment that utilizes the techniques it supports. In addition, many of the parameters specified in the above SLL script are ambiguity in the specification and the use of SSL scripting in combination with other aspects of the invention of this disclosure. It is important to note that this is something that can be neatly resolved by using If the user wishes to run the same experiment again, all he needs to do is To extract accurate parameters, we first extract the objects associated with the experiment, e.g., tocol[123141,qPCR], and therefore the experiment It is possible to obtain a truly complete description of all steps used in a qPCR experiment. Calling a function. The function call is very small, despite its completeness. Example For example, Experiment qPCR takes 42 parameters. A mere 12 more parts were added to override the defaults that were resolved into the system to meet the specifications. parameters are specified by the user. They can be user or system specified. Even if it were, the system would still store the values ​​used for all 42 parameters. Remains.

[0088] Additionally, the remainder of the experiments disclosed herein can also be expressed in SLL script. However, for the sake of brevity, this is not done here. I am not aware of any system that can do this and scale well. The fundamental point is that We pursue a wide range of scientific questions, including fundamental research and development, and The invention is highly flexible and allows for a wide range of experiments to be displayed and performed. . [Generation of experimental protocol]

[0089] In some embodiments, once the design of the experiment is completed and submitted by the user, The system then generates an Experiment Protocol object based on the design, which is In some embodiments, the completeness of the parameter resolution may be By assumption, protocol objects can also be considered to be computationally complete, i.e. That is, the Protocol Object requires further user input to describe the intended experiment. Instead, the instrument (and optionally the technician) acts as a set of instructions for carrying out the experiment.

[0090] In some embodiments, a system is used to generate experimental protocols for use in a laboratory. The system processes protocol objects and assigns steps, samples, reagents, and / or tasks. Task scheduling (e.g. parallel processing, equipment availability, potential bottlenecks, Resolve dependencies between different equipment (e.g., physical distance between instruments in a laboratory, relative sample locations, etc.) Generate an experimental protocol to be followed in the laboratory. This solution is done using a protocol object. available to the part of the system that created the document (e.g., the user's local computer) This experimental protocol may require information not related to the control of the robot and / or equipment. API (Application Program Interface) calls to , including machine code, such as itemized instructions that can be executed by a human being if necessary. In some embodiments, when a protocol object is created, A protocol is generated and included in a protocol object. In a preferred embodiment, The protocol objects are then processed by the orchestration module associated with a particular laboratory. When an experiment object is processed, an experiment protocol is created. The configuration can be done on any computer, e.g., the user's computer, a remote computer server, The processing of protocol objects may occur on a computer located in a remote server or in a laboratory. Also, any computer, e.g., a user's computer, a remote computer server This may occur on a computer located at a server or in a laboratory.

[0091] In some embodiments, the user interface includes a step of retrieving a reagent from storage. To provide instructions regarding specific steps that may need to be performed by a technician, such as Thus, in some embodiments, the instructions The itemized list may be presented to the technician continuously, optionally upon completion of each order. The system receives a confirmation (e.g., by scanning a bar code on the reagent packaging). by the technician) or by the instrument (e.g., by indicating that the sample has been loaded). This can be done automatically from the device that detects the

[0092] The Protocol object coordinates the design, execution, and data recording of an experiment. As provided, protocol objects are generated pursuant to the execution of an experimental function. The protocol object then creates the corresponding sample object. It may also direct and coordinate the creation of new physical samples, including The object directly or indirectly interacts with the equipment and / or technician. It can run experiments, monitor the process of the experiments, and record data generated from the experiments. [Run the experiment]

[0093] The system of the present disclosure can be configured according to the needs of its user. In this system, systems are interconnected or connected to a central server. or multiple computers (shown as workstations in FIG. 18). The data source, such as a database, may be located on one of the computers, but preferably is It may be located on a remote server, such as one in a data center.

[0094] The system may include one or more laboratories (shown as laboratories in FIG. 18) having scientific instruments. Each laboratory and its equipment may also include one or more computers in the system. In one embodiment, the system communicates electronic data with the computer for each type of experiment. At least one laboratory is responsible for, for example, synthesis, purification, amplification, quantification, cell culture, and analysis. In one embodiment, the system includes at least purification, amplification and quantification experiments. In one embodiment, the system includes at least one purification, quantification and cell culture device. In one embodiment, the system includes at least purification, analysis, and cellular Includes cell culture laboratory equipment.

[0095] In some embodiments, the laboratory equipment performs at least HPLC, PCR, and culture. In one embodiment, the system further comprises a liquid handling station. , flow cytometers, centrifuges, DNA synthesizers, pH meters, and microscopes.

[0096] In some embodiments, the system further comprises a variety of sensors for monitoring the experimental environment. , and HVAC (heating, ventilation and air conditioning) systems for controlling the environment. In one embodiment, the system includes at least a temperature sensor, a pressure sensor, a humidity sensor, and and / or optical sensors, each of which is connected to the system's computer. In a related embodiment, the sensor data is collected before, during, and / or after the experiment. , and record it in conjunction with the experimental data for future data analysis and troubleshooting. will be done.

[0097] The program code, compilers, and analyzers are stored in one or more computers. It can be used to enable operation, monitoring, data collection, and analysis of the equipment. In this program, the program code allows users to design and run experiments, monitoring experiments, and reviews. The system is presented to present a graphic user interface that allows the analysis of test results. The program code, analyzer, or compiler constitutes a system, which is illustrated in the figure. , need not be stored locally on the computer executing any aspect of the system. [Data Integration Module]

[0098] Figures 8, 9 and 10 show some of the data visualizations generated by the system. Such interfaces are used to communicate with the various objects in the SLL system. The software is made available through the use of modules, programs, and functions (also referred to herein as "modules"). Non-limiting examples of objects and functions include "experiment," "data," and " Analysis, Sample, Equipment, Control, Inventory, Maintenance, Operator, Company ","Model,","Report,","Calibration,","Container,","Method,","Model,","Part" "Products", "Programs", "Protocols", "Sensors", "Simulations", and and "environment." Often, terms are associated with objects and functions. For example, there can be both experiment objects and experiment functions.

[0099] The "experiment" module is designed to display information about experiments. As illustrated in FIG. 9, the “experiment panel” 901 is ,Any image for easy identification of the experiment type (e.g., flow cytometry) 902. Additionally, the information displayed on the panel may include (column 903 is information type, and column 905 has details). - Operator: The person who operates the experiment - Instrument: The equipment on which the experiment is performed - Samples In: Samples used in the experiment - Data: Data generated from the experiment - Environmental: Measured environmental data, e.g. in a laboratory Identifier for environmental records showing temperature, air pressure, and humidity - Date: Date and time of the experiment - Other information specific to this type of experiment, e.g., flow rates and flow paths

[0100] Each of these classifications of information has links that lead to different modules or other calculations. Note that a user may embed an instrument. For example, When you click on line 905, the Instrument module (more on that below) will be called and will show a new panel with information about the equipment used in this experiment. Wax.

[0101] "Data", alternatively called the "Analysis" or "Plot" module The module displays data generated from an experiment on a panel (e.g., data panel 801 in FIG. 8). The method is configured to display a visualization of at least a portion of the data set. Typically, there are multiple ways to extract relevant data for analysis and multiple ways to analyze and There are various ways to visualize the data. In one embodiment, the data module is The method of data extraction, analysis and visualization may be automatically determined; also allows the user to employ other available methods.

[0102] For example, it will be appreciated that the data in Figure 8 is taken from a flow cytometry data set. By default, the data module will use the on-the-fly data from this particular dataset. Generate a scatter plot "802" at the appropriate scale determined by (a). This function is often Note that this is subject to accurate parameter resolution. For more complex specific experimental data, , 1 more data entry (e.g. multiple entries on the panel of an experiment module and ) can be generated, each of which provides the user with a different data analysis or visualization panel. results.

[0103] Similar to the experiment panel, the "data" panel contains information about the data. (See column 803 for information type and column 804 for further information). - Experiment: The experiment from which the data was generated - Figures: Diagrams generated from the equipment or data in an experiment. - Analysis: The analysis available for the data. - Date: Date and time of the experiment - Other information specific to this type of data, e.g. gating, clustering

[0104] Each of these categories of information also contains links to other modules or other For example, if a user selects row 805 of Experiment, When clicked, the experiment module will be called and will display information about the experiment. .

[0105] The Analysis module provides data analysis and related Display related visualizations. - Source Data: The data used to generate the analysis. - Processed Data: Data that is processed for the purpose of the analysis. Data - Figures: Figures generated from the analysis - Date: Date and time of analysis - Other information specific to the analysis, e.g. technical details of the analysis (e.g. clustering analysis) , K-means for clustering, and Euclidean distance for similarity measurement)

[0106] Each of these categories of information also contains links to other modules or other For example, the user can input Source Data. When you click, the system displays information about the data used for the analysis, such as the data It will be displayed in the module.

[0107] The "Sample" module is designed to display information about a sample. It is made up of samples, bases, and samples provided by the customer and received in the laboratory. The information may be provided by the data subject or generated from experiments. may include, for example: - Supplier: The person or company that provided the sample - Experiment: The experiment to be performed on the sample - Source Experiment: The experiment from which the sample was generated - Container / Location: The location where the samples are stored. Container and / or location identifier - Model: An entity with samples and associated fields, parameters, etc. Type (e.g., chemical structure, protein sequence, cell type) - Control: Identifier of the appropriate control sample - Date: The date and time the sample was generated or received. - Other sample specific information, e.g. type, solvent, concentration

[0108] Each of these categories of information also contains links to other modules or other For example, the user can select Source Experiment. When you click the Sample Experiment field, the system calls the experiment module and The pull will display information about the experiment that was generated.

[0109] The "Instrument" module is designed to display information about the instrument. As shown in FIG. 10, the information displayed on the panel 1001 is, for example, , may include the equipment illustrated in image 1002. - Model (see column 1003): the device manufacturer's model number (see column 100 4) (not to be confused with model objects or the general model concept of SLL) - Experiment: A list of experiments performed on the device - Maintenance: A list of maintenance carried out on the equipment - Controls: Control experiments / samples performed on the instrument - Data: Data set generated from experiments performed on the instrument. - Date of Installation: Date of installation of the equipment. Date and Time - Visualization: Image of the device - Manual: Manual document - Other information specific to the device, e.g. serial number, software

[0110] Each of these categories of information also contains links to other modules or other For example, the user can list under Experiment When you click on an experiment, the system calls the experiment module and It will display information about the experiment. Due to the linked nature of the objects, (protocol[123,Western][SamplesIn], or equivalent , SamplesIn / .Info[protocol[123,Western]]) See all samples from or run on Western Data Mass Spectrum Peak picking analysis (protocol [123, Western] [Dat a][PeaksSourceSpectra], or equivalently, PeaksSourc eSpectra / .Info[Data / .Info[protocol[123,W estern]]]) It's easy.

[0111] The "control" module is used for calibration and / or quality control purposes. configured to display information about control experiments performed on one or more samples on the instrument; In some embodiments, the control module is an experiment module that displays a control experiment. The control module may show information including, for example: - Sample: A sample used to perform a control experiment. - Instrument: The instrument on which the control experiment was performed - Result: indicates whether the control experiment was successful or unsuccessful - Data: Data generated from controlled experiments - Expected Values: The expected value for a particular data point in the results. The expected value or range of values - Visualization: Data visualization from data - Date: The date and time the control experiment was performed - Other information specific to the control experiment, e.g., type of control

[0112] Each of these categories of information also contains links to other modules or other For example, when a user clicks on an instrument, When the device is connected, the system will call the device module and display information about the device. .

[0113] The "inventory" module is a set of users (e.g. a company) Display information about the user, samples, experiments, and / or data inventory. The inventory module may show information including, for example: - Sample: A sample provided by or for a user or group of users. List of samples generated for - Experiments: Experiments designed by a user or a group of users or a list of experiments to be performed on it - Data: Data generated from the enumerated experiments - User: A user or a group of users (e.g. a company) - Other information specific to the inventory, e.g. time of last edit

[0114] Each of these categories of information also contains links to other modules or other It is possible to embed a calculation function. For example, when the user clicks on sample, When a sample is selected, the system will call the Sample module to display information about the sample. Wax.

[0115] "environ" module, sometimes also called "sensor" module The "environment" module displays the environmental information collected when an experiment was run. Environmental factors such as temperature and air pressure in the laboratory can affect the experiment. However, it should be understood that there is a lack of a well-integrated system, and The lack of awareness of the importance of these factors is likely due to a lack of awareness of such environmental factors. Children often need to remember when they designed, performed, and recorded their experiments. In this technology, environmental variables are strictly controlled, and their details are not considered. Non-limiting examples of environmental factors include temperature, air pressure, humidity, and light. and air purity (e.g., PM2.5). The system is configured to display measurements related to one or more environmental factors and to Factors can be of a general or local nature, e.g. , the temperature in the laboratory relative to the temperature in the vicinity of a particular liquid handler.

[0116] The system also includes, but is not limited to, the following modules: "Maintenance" module to display information about the entity (e.g. For example, chemical structures for chemical samples, protein sequences for protein samples, A "Model" module for displaying the cell types for a cell sample, A "report" module for displaying aggregate information about any issue in the system, such as literature tool, displays information for the operator to run the experiment (e.g., loading samples onto the system) and an "operator" module for identifying the ) Includes a "Company" module to display [Data exploration and visualization]

[0117] The integrated laboratory system and data integration module allows the system to be managed in a user-friendly manner. Allows users to examine any data associated with an experiment collected by the program. Some examples are illustrated in Figures 14 to 17. The following examples are based on the The method is presented in a manner that requires user interaction via a global user interface. In a graphical user interface, the user can select specific displayed information for a module. by clicking on a link or using other input mechanisms. Thus, one may interact with the system. However, such examples are for illustrative purposes only. However, the investigation of data in a system does not necessarily require visualization, much less graphical visualization. It will be readily understood by those skilled in the art that it is not necessary to Guidance through the wire also does not require any mechanical action by the user, but is instead expressed as a machine-readable code or It can only execute commands. So the click in the following example calls a function. This may be understood as calling or executing a command.

[0118] In Figure 14, we call the experiment module for the project. The user can then trigger a command (e.g. click or run the appropriate script) to When you open the panel (by entering In this example, the experiment was performed using flow cytometry. On the panel, the user can select the data generated from the experiment. The user can click on the link embedded in the text that shows the data (see the second to last lines of FIG. 9). ), the data module is called, and a new panel (the data panel, See also FIG. 8).

[0119] The data panel displayed by the data module is In addition to the event information links, an optional diagram “802” is shown. The diagram shows all the diagrams generated from the experiment. The data need not be represented. Moreover, in some embodiments, the figures may provide an overview of the data. Therefore, its generation does not require user input. The system automatically selects data extraction / transformation and visualization techniques to present the data. For example, for flow cytometry data, the data module automatically Select a scatter plot and scale that will accommodate at least 95% of the available data points.

[0120] Like the Experiment Panel, the Data Panel also contains links to other modules / panels. Link 805, for example, points the user back to the experiment panel.

[0121] Because a data set can be analyzed in multiple ways, the Data Panel supports multiple analysis modules. It also contains links to multiple instances (the two analysis modules in Figure 14). One analysis here is regarding gating. The other analysis involves clustering. When called, the analysis module The information displayed may include, but is not limited to, the following: data, details of the analysis method, and analysis results.

[0122] In addition to generating analytical panels with little or minimal user input, From the collected data set, the system can also generate reports from the analysis results. When a user clicks on a report link in any of the analytics panels, the reporting module You will be presented with a panel showing the port (report).

[0123] In one embodiment, the report panel displays a collection of information about the experiment. As such, and unlike previous reports, the reporting panel herein is an integrated data source. It can be dynamic, since it is supported by a network and connected to laboratory equipment.

[0124] For example, FIG. 12A shows a dynamic diagram that may include analysis and reporting panels. , a time-dependent concentration curve (1204) is shown for the enzyme kinetics simulation, It can be used for comparison with actual experiments. The upper part of the curve has a user-modifiable Three possibilities are available to allow you to see the immediate simulation results of your changes. Even on a curve, the user can move the cursor to a specific point (e.g., 12 05), the user can fine-tune the curve to suit their needs. A script 1201 is used to generate the visualization, and the script is It may also be appreciated that any intentional changes may result in an update or regeneration of the visualization.

[0125] Figure 15 shows how to test the equipment used in an experiment and then perform a control experiment on the equipment. Here's another case where the user clicks on the experiment panel. can be the closest control experiment before the actual experiment is performed, or it can be the most recent The control experiment may be a control experiment performed shortly (including after) the experiment. If the instrument can handle a variety of sample types and experiments, control experiments can be performed. This is the same type of experiment as in the previous one.

[0126] In Figure 16, the user selects When you click on the link to the sample (cell sample) used, The user then selects the different experiments to be performed on the sample. The staining experiment panel then allows the user to select the dye to be used for staining. Different samples (e.g. chemical samples) The sample panel allows the user to create a model that shows a chemical structure. Re-access vendor information on the Dell panel and vendor (company) panel. and other information about the chemical entities of the chemical sample (e.g., chemical In turn, the researchers can access the mass spectrometry data available to the researchers. The chemical samples for this chemical entity were collected from the pull panel and the model panel, respectively. The user is prompted to enter data to display the NMR data for the sample and associated control sample. Click on the (data) and control links.

[0127] The example in Figure 16 highlights the ability of the system to correlate different experiments with shared samples. However, the example in Figure 17 illustrates the system's ability to perform compound experiments.

[0128] In FIG. 17, cell sample 20943 is subjected to a flow cytometry experiment. The cells collected after the flow cytometry experiment were then subjected to cell staining experiments. Identify a cell (19423) as the power. These output cells are then used in the cell division experiment. The identified samples are then analyzed to generate data and data analysis. (model 21). Users are encouraged to learn more about cell types. If the model has a heart, the user clicks the report link on the model panel. You can find bibliographic information by clicking on it.

[0129] All these and other features are partially represented in Figure 11, where each dotted line represents The user navigates between panels connected by links presented on these interfaces. The interconnections of the system are summarized in Figure 13. It can be done.

[0130] 12B and 12C show two plots showing the advantages of the present technique over the prior art. In the plot PlotMassSpectrometry in Figure 12B, The line (indicated by the arrow) shows where the system estimates the peak should be. This is only possible through the integration of experimental design, execution and analysis. The assSpectrometry function returns the raw mass spec data leading to a plot. Access the data object that contains the data and the subobject associated with the data object. dereference the link to the sample object, then the model associated with the sample. The modified reference links to the object (the model contains the putative nucleic acid sequence of the sample). and then calculating the molecular weight of the sample based on the information in the model object. and calculating the molecular weights of n-1, n-2, and n-3 truncated versions of the sample. For example, if the model indicates that the sample is ATGCATATGC, then The models are ATGCATATGC, ATGCATATG, ATGCATAT, and AT Calculate the molecular weight with respect to GCATA. This allows the synthesis process to be terminated quickly in some cases. Therefore, the samples are of shorter duration. There should be peaks corresponding to the strands. For visualization purposes, use PlotMassS The spectrometry function then plots the area around the calculated expected molecular weight of the sample. Place it in the center of the rough. Such a consolidation is possible, for example, if someone illustrates this plot years from the present. We want to plot the underlying sequence of samples that were analyzed, and then It would also be advantageous for him to resynthesize the pool for use in his own experiments. This is somewhere between extremely difficult and impossible in the art, but the invention of this disclosure It is borderline trivial to run with For example, data[38913,MassSpectromerty][Samp lesIn][Model][Strand] can be achieved, or equivalently, Stra nd / .Info[Model / .Info[SamplesIn / .Info[dat a[38913,MassSpectromerty]]]] gets the sequence, This can then be input into a new synthesis experiment.

[0131] Such advantages arise from one embodiment of the presently disclosed system being tightly integrated with the analytical instrument. The ability to trace data back extensively to the facility that set up the experiment that generated it. It is possible to explore the experimental features and settings of the user interface. The preliminary parameter check ensures that all of the necessary information is collected when the experiment is set up. Such integration helps ensure that experiments are performed and to ensure that the analysis of the resulting data can be carried out with such assurance and to develop stronger analyses. It can support analytical experiences.

[0132] Another example highlighting the benefit of integration is the PlotQuantificat ionCycle plots, where we use the plotting function accesses the experimental protocol and extends the number of cycles specified for the experiment, After that, upper and lower bounds (indicated by arrows) are set based on the actual number of cycles performed. ) is set. Since the function knows that only n cycles have been performed, The rest can be considered to be fake. By discarding the fake data, the proper Improved automatic calculation of inflection points (circles).

[0133] Thus, in one embodiment, the data analysis method of the present disclosure is ) analysis includes reference data that are not generated directly from the current experiment. One example of such reference data is data provided by or available from the user. calculated by the system using input from the user or without any input from the user It may be the value of an experimental parameter, either calculated by the system. Another example of such reference data may be information about the device, such as how the device is calibrated. do.

[0134] Yet another example of such reference data may be the environmental conditions in which the current experiment is performed; These include, but are not limited to, temperature, brightness, and humidity. The data is from experiments that preceded the current experiment, preferably related to the current experiment. It is also important to draw on any information regarding such prior The experiment may generate samples used in the current experiment, which may be Analyze experimental samples or reveal the current status of an experiment. In some cases, reference data may impose limitations on the interpretation of the current experiment and may provide a basis for clarifying the results of the current experiment. To improve the quality of the data (e.g., by removing irrelevant, invalid or less important parts of the data) are used to remove the In some embodiments, data from prior experiments are used to interpret the results of the current experiment. is used.

[0135] In one embodiment, the present disclosure provides a system for developing a scientific experiment. The system consists of memory, a processor, a device, and a specific software environment, as well as modules. As illustrated in FIG. 19, the system 1900 can be conceptually divided into two parts: Some modules may be located on the client computer (1901). However, some modules are considered more directly relevant to the laboratory setting (1902). They may be connected to a database (1903) on a remote server. As will be readily understood by those skilled in the art, the configuration illustrated in FIG. 19 is for illustrative purposes only. , is not intended to limit how the system may be configured.

[0136] In one embodiment, the system includes an experiment module (1904), a parameter solution module (1906), The system includes a user interface module (1906), and a user control module (1907). In some embodiments, two or more experiment modules are implemented in the system's software. Each of these is included in a database-based development environment, and each of these is configured with one or more parameters and The parameter includes one or more criteria, and the parameter is used to perform an experiment. The method is configured to generate a plurality of instructions for performing the technique.

[0137] The experiment module 1904 provides commands to perform two or more experimental techniques. The system may present a user interface (1907) that can be received from the user. The interface module 1906 communicates with the lab. Each command relates to one of the experimental techniques. These input values ​​may include input values ​​for one or more parameters that The parameter resolution module (1905) may refer to the parameter resolution for the data resolution. For example, for each parameter for which an input value is received, a parameter resolution module A determination is made as to whether the input value is valid based on at least one of the criteria related to the meter. Such decisions may also obtain information from the experiment module. For each parameter that is not computed but is available, the parameter resolution module The value is calculated based on at least one of the criteria for the parameter. The data resolution module generates a warning if at least one parameter is missing an input value. possible.

[0138] When solving for parameters, one experiment, or in certain embodiments, two or more Many experimental techniques can be stored and executed. The information is then sent to other parts of the system. The execution of the experiment may be performed by storing the results of the experiment in a database (1903) from which the results of the experiment may be obtained. A technician (1 910) and is coordinated by the Orchestration Module (1909) The orchestration module also monitors various experiment and environment states. The experiment is carried out in a laboratory-like manner. It is controlled by an execution module (1911) that makes calls to various devices (1913). The data is then sent to the reporting module (1912), which then transmits the data or reports to the reporting module (1912). Each of the modules interacts directly or indirectly with the orchestration module. It can work.

[0139] A system such as that illustrated in FIG. 19 may be used to perform two or more experimental techniques, or alternatively , 3 or more, 4 or more, or 5 or more experimental techniques In some embodiments, the experimental technique may be adapted to include analytical balance readings, Apoptosis analysis, autoclaving, buffer preparation, centrifugation, DNA / RNA synthesis, precipitation Fluorescence microscopy, fast protein liquid chromatography (FPLC), flash chromatography Chromatography, flow cytometry, fluorescence kinetics, fluorescence polarization, fluorescence spectroscopy, fluorescence thermography Mechanics, Genomic DNA preparation, HPLC (ion exchange), HPLC (reverse phase), Light microscopy , liquid handling, freeze-drying, MALDI mass spectrometry, mammalian cell culture, pH reading, polyacrylamide Polyacrylamide gel electrophoresis (PAGE), polymerase chain reaction (PCR), protein Extraction, quantitative real-time PCR (qPCR), RNA extraction / cDNA preparation, rotary evaporation, Solid phase extraction, Speedvac concentration, thermometer reading, thin layer chromatography (TLC), Total protein amount, gene transfection, UV / Vis kinetics, UV / Vis spectroscopy, UV / Vis Thermodynamics, Vacuum filtration, Virus preparation, Volume check, Western blot, Agarose gel Electrophoresis, Arabidopsis studies, atomic absorption spectroscopy, atomic emission spectroscopy, atomic force microscopy , bacterial cell culture, bioreactors, bomb calorimetry, C. elegans research, capillary electrophoresis Electrophoresis, circular dichroism (CD), colony picking, confocal microscopy, cross-flow filtration (TFF), crystallization, dialysis (equilibration), dialysis (formulation), differential scanning calorimetry (DSC), digital Droplet PCR, DNA sequencing (next generation), DNA sequencing (Sanger), Showa fruit fly research, dynamic light scattering (DLS), electron microscopy, electroporation, electrospray ESI mass spectrometry, enzyme-linked immunosorbent assay (ELISA), flow chemistry , Fluorescence Activated Cell Sorting (FACS), Fluorescence in Situ Hybridization (FISH), Gas Chromatography Chromatography, Gas Chromatography-Mass Spectrometry (GC-MS), HPLC (normal phase) , HPLC (preparation), immunoprecipitation, inductively coupled plasma mass spectrometry (ICP-MS), infrared spectroscopy, isothermal titration calorimetry (ITC), liquid chromatography mass spectrometry (LC-MS), Liquid-liquid extraction, melting point determination, microarray analysis, microwave reaction, molecular cloning, N MR (2D / structural), NMR (carbon), NMR (proton), organic synthesis (milligrams to gram scale), patch clamp recording, peptide synthesis, photostimulated luminescence (PSL), Smid construction, refractometry, scanning tunneling microscopy, solubility testing, sonication, Supercritical Fluid Chromatography (SFC), Surface Plasmon Resonance (SPR), Tandem Polymerization Mass spectrometry (MS-MS), tissue homogenization, total internal reflection fluorescence (TIRF) microscopy, and ultracentrifugation. The method is selected from the group consisting of isolation methods, X-ray crystallography, and yeast cell culture.

[0140] In some embodiments, one of the conditions is that no alerts are generated. In some embodiments, one of the conditions is that only non-critical warnings are generated. It is possible to do so.

[0141] In some embodiments, the execution module further transmits back the received command. In some embodiments, the execution module is configured to generate an object that The generated executable program is then executed to execute the experimental technique specified by the received command. The object is configured for use in a physical laboratory.

[0142] In some embodiments, the system further comprises: In some embodiments, the method further comprises: The system further comprises displaying a portion of the received data in a software-based development environment. In some embodiments, the system further comprises a module for displaying the Module for analyzing a portion of received data in a software-based development environment - Patents.com In some embodiments, the system further comprises: In some embodiments, the method further comprises: The system further receives one or more additional executable commands from the user after receiving the data. The device has a module for receiving the signal.

[0143] In some embodiments, the software-based development environment generates executable commands. In some embodiments, the software base includes a graphical element for selecting the The development environment of the source includes functionality for graphically displaying the received data.

[0144] Another embodiment of the present disclosure is a system for analyzing data obtained from laboratory experiments. The system includes a processor, a memory, and one or more of the following: and program code including a number of modules. 20A, 20B, 20C, 20D, 20E, 20F and 20G. do.

[0145] For example, in FIG. 20A, the user launches the plot module (2008) and A data object (2004) containing data generated by a specific experiment is accessed. The plot module uses the protocol object of the data object (2002). Access the link to identify the protocol object and retrieve the information you need from the protocol. It is similar to the way that data objects are retrieved from analysis objects. (2003) and sample objects (2005) to access the links It also identifies and retrieves information from sample objects. Follow the links in the project to identify the relevant information you need and The plot module (2007) is taken from the environment module (2006). The plot module receives information about the desired plot. In one embodiment, the environmental module returns the information to the user interface (2008). Instead, the environment object is accessed through a similar link structure. be.

[0146] Figures 20B to 20G show the analysis (2009) and simulation module execution. In a preferred embodiment, the plot, analyze, and and Simulation Module (2010) access the link only when necessary. For example, if a module already has enough information to resolve a parameter, it Optionally, a potentially related link (if it is indicated in the object) Those skilled in the art may have access to more than just the above-described embodiments. , additional links to additional objects may perform the same set of operations as described herein. It is easy to understand that the information can be displayed and accessed by modules as needed using the For example, a data object may be a set of objects from which an analysis module can extract information. This may potentially indicate multiple sample objects that may be determined and acquired.

[0147] Additionally, in some embodiments, a module may operate in conjunction with another module. For example, an analysis module may call a plot module to display the output of the analysis module. It can be plotted.

[0148] In some embodiments, the system 2000 may include a processor 2004 for controlling the experimental parameters for performing an experiment. Each experiment module includes one or more experiment modules configured to store a value of the experiment data. The rule is to separate experiments (or experiment techniques) so that multiple experiment modules can represent multiple experiments. Alternatively, an experiment module may represent more than one experiment. It can represent an experience.

[0149] Additionally, a data module may be included in the system and configured to store the results of the experiment. In some embodiments, the data stored in the data module also includes an experimental model. In one embodiment, the system may include: an equipment module configured to store information about the equipment on which the experiment was performed, An experiment may involve more instruments, which may be represented by one or more instrument modules. Possible.

[0150] Additionally, in another embodiment, the system may be adapted to store the environmental conditions under which the experiment was performed. Includes configured environment modules. Examples of environment conditions are described above.

[0151] Without limitation, the system may include a data analysis, exploration, or visualization module. A data analysis, exploration, or visualization module may also be included to analyze and visualize data from the experiment. In one embodiment, the analysis or visualization is performed by a digital The results are based on the results stored in the data module, but may also include one or more reference data points or other It may further include representations thereof from data sources. Examples of such data sources are experimental A data module, a data module, an equipment module, or an environmental module. For visualization purposes, the reference data points are displayed on the user interface together with the results from the experiment. It can be shown.

[0152] In some embodiments, the reference data point is a second data point associated with the experiment being analyzed. In some embodiments, the relationship is that the reference data point is It places limitations on interpretation. For example, a reference data point may be one that is not relevant to the analysis of the data. As a result, it helps to exclude some of the results, validates or invalidates the results, and applies targets to the results. Act as a benchmark or control.

[0153] In another embodiment, the present disclosure provides a method and apparatus for implementing the present invention, comprising: A system for analyzing data obtained from laboratory experiments, comprising: The code includes an identifier for the sample used in the experiment, an identifier for the equipment used to perform the experiment, and ,An identifier for the dataset generated from the experiment, and when and where the,experiment was performed. an environmental record identifier including a measurement of the environmental condition of the A data extract or visualization to represent the dataset and the implementation that generated the dataset. Data structured to display the identifiers of the experiments and the analyses that were performed on the dataset. A list of experiments performed on the module,equipment and a list of control experiments performed on the,equipment and an equipment module configured to display the maintenance records for the data set on which the analysis is performed; and an analysis module configured to display an identification of the analysis result and an analysis summary or diagram representing the results of the analysis. It is configured to display the rules and environmental conditions of when and where the experiment was run. The system includes an environment module, and the user can select an experiment to be displayed by the experiment module. While being presented with a panel, (1) the user provides an identifier for a dataset that will be generated from the experiment. Allows you to click on the experiment panel and thereby call up the data module. to display the identifiers of the analyses to be performed on the dataset on the Data Panel, and allows the user to click on the identifiers of the analyses that have been performed on the dataset, Invoke the analysis module and display an analysis summary or chart on the analysis panel that shows the results of the analysis. (2) enable users to click on the identifiers of environmental records, ,The ,environment ,module ,is ,called ,to ,represent ,the ,environment ,state ,of ,when ,and ,where ,the ,experiment ,was ,running. and (3) the user clicks on an instrument identifier to run the experiment. This allows the instrument module to be called to execute control runs performed on the instrument. By displaying a list of experiments and maintenance records for equipment related to the experiment on the equipment panel, This allows the user to explore information about the experiment.

[0154] In some embodiments, the program code further comprises: a sample display configured to display an identifier of a first experiment and an identifier of a second experiment performed on the sample; It has a loop module.

[0155] In some embodiments, the analysis summary or diagram displayed on the analysis panel is The user has control over and access to the dataset from which the requirements or figures are generated. This makes it possible.

[0156] In some embodiments, the system comprises one or more devices running the comparison Allows users to click on the experiment listing on the instrument panel to view multiple other experiments. To perform.

[0157] Although the above discussion may refer to a particular order and arrangement of method steps, these It is understood that the order of steps may differ from that described. For example, two or More steps may be performed simultaneously or partially simultaneously. Some steps may be combined and may be performed simultaneously or in conjunction. The steps performed may be separated into individual steps and the sequence of certain processes may be reversed. may be modified or otherwise changed, and the nature or number of individual processes may be modified. The order or sequence of any elements or devices may be changed in alternative embodiments. may be modified or replaced by any of the following: Such modifications are intended to be within the scope of the present invention. The software and hardware systems are subject to the designer's choice. All such variations are understood to be within the scope of the invention. Software and web implementations of the invention may be implemented using standard programming techniques. to accomplish various database search, correlation, comparison, and decision steps. This would be the logic behind it.

[0158] Unless otherwise defined, all technical and scientific terms used herein are The terms have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Has a taste.

[0159] The inventions illustrated by way of example herein do not include any element not specifically disclosed herein. Alternatively, the invention may be practiced without any element, limitation, or limitations. The words "comprise," "include," "have," and the like are to be read expansively and without limitation. Moreover, the terms and expressions used herein are not intended to be terms of limitation. They are used as terms of description and therefore the use of such terms and expressions is , without evidence of any intention to exclude any equivalent of the features shown and described, or portions thereof. Rather, it is recognized that various modifications are possible within the scope of the invention as claimed. do.

[0160] Likewise, the present invention is specifically disclosed by preferred embodiments and optional features. However, the knowledgeable reader will appreciate modifications, improvements and variations of the subject matter embodied herein. It is believed that these modifications, improvements and variations are within the scope of the invention.

[0161] The invention is described broadly and generically herein. Narrower terms that fall within the generic disclosure are not intended to limit the scope of the invention. Each of the classifications and subgroupings also form part of the present invention. or removing any subject matter from a genus, regardless of whether the removed material is specifically described. The invention shall include a comprehensive description of the invention, together with any applicable qualifications or negative limitations.

[0162] When a feature or aspect of an invention is described by reference to the Markush group, The explanation also applies to any individual member or subgroup of members of the Markush group. This is explained by that.

[0163] All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. by reference in their entirety to the same extent as if each was individually incorporated by reference. It is expressly incorporated herein. In case of conflict, the present specification, including definitions, will control.

[0164] Although the present invention has been described in conjunction with the above-mentioned embodiments, the foregoing description and examples disclose The present disclosure is intended to illustrate the scope of the present invention and is not intended to limit the scope of the disclosure. Other aspects, advantages, and modifications within the scope will be apparent to those skilled in the art to which the disclosure pertains. It would be white.< / type> < / type>

Claims

1. A data set obtained from laboratory experiments, comprising a processor, memory, and program code. a system for analyzing data, the program code being executed by the processor; When executed, the system storing values ​​for experimental parameters for carrying out the experiment; storing results from said experiments; storing information about the equipment on which the experiment was performed; storing the environmental conditions under which the experiment was performed; At least some of the results from the experiment or at least some of the experimental parameters adjusting one or more experimental parameters based on one other parameter; the one or more adjusted experimental parameters or the values ​​for the experimental parameters; The information about the device, and the environmental conditions. selecting a visual representation of the result based on the data points; A system that executes the above.

2. The selection of the visual representation may further depend on the protocol used to perform the experiment. The system of claim 1 ,

3. The selection of the visual representation comprises: determining a range of the visual representation based on the protocol; and generating the visual representation based on the determined range; and The system of claim 2 further comprising:

4. The selection of the visual representation comprises: estimating one or more peaks associated with the results based on the protocol; and centering the visual representation about the estimated peak or peaks; 、 The system of claim 2 further comprising:

5. A data set obtained from laboratory experiments, comprising a processor, memory, and program code.

1. A system for analyzing data, comprising: An identifier for a sample to be used in an experiment, an identifier for an instrument for carrying out said experiment, Identifiers for the datasets generated from the experiment and when and where the experiment was performed and an experiment model capable of displaying one or more of: Jules and A data extract or visualization for representing a data set and a method for generating the data set. an experiment identifier; and an analysis identifier performed on the dataset. A viewable data module; A list of experiments performed on the device, a list of control experiments performed on the device, and and a maintenance record relating to the vehicle; An identifier for the dataset on which the analysis was performed and an analysis summary or diagram representing the results of said analysis; an analysis module capable of displaying one or more of the above; an environmental module that displays the environmental conditions when and where the experiment was performed; The system allows a user to be presented with an experiment panel displayed by the experiment module. While (1) the user provides the identifier of a dataset generated from the experiment to the experimental panel; by clicking on the mouse, thereby invoking the data module, displaying on a data panel an identifier for an analysis to be performed on the data set; The rule allows the user to click on the identifier of an analysis that has been performed on the data set. and invoking the analysis module to generate an analysis summary or diagram representing the results of the analysis. Displaying it on the panel; (2) enabling the user to click on the identifier of an environmental record, thereby The environment module is then called to obtain the environmental conditions of when and where the experiment was run. and displaying the state of the (3) the user clicking on the identifier of the device for performing the experiment; , thereby invoking the instrument module to execute controls performed on the instrument. Displaying a list of experiments and maintenance records of said equipment associated with said experiments on an equipment panel. and enabling the user to explore information about the experiment; The system further comprises: based on at least one other parameter of the one or more experimental parameters, Adjusting one or more experimental parameters; system.

6. The analysis module is further capable of displaying the graph representing the results of the analysis; The representation of the diagram is based on the protocol used to perform the experiment. The system described.

7. The analysis module further includes determining a range of the diagram based on the protocol. and displaying the diagram based on the determined range. The system described in

8. The analysis module further determines one or more of the following related to the outcome based on the protocol: A plurality of peaks are estimated, and a visual representation is centered around the estimated peak or peaks. The system according to claim 6 or 7, wherein the system is capable of performing a plurality of operations.

9. The program code further includes: Steps for receiving a selection of samples; removing experiment types that are incompatible with the received sample selection; submitting the remaining experiment types excluding the incompatible experiment types; Prompting a user to provide an input of a selected experiment type from the remaining experiment types. The procedure to receiving said input of said experiment type; In response to receiving the input of the experiment type, the user determining a subset of parameters that are more suitable for input by the user; highlighting said subset of said parameters; The user is prompted to provide one or more entries for the subset of parameters. and receiving the one or more entries into the subset of parameters; performing the experiment based on the received entry or entries; The system according to claim 1 , further comprising:

10. The selection of the visual representation may further comprise: one or more sequences corresponding to the molecular weight of the sample and one or more truncated versions of the sample; a step of estimating the estimated molecular weight of the number of The estimated molecular weight of the sample and one or more truncated versions of the sample. and estimating one or more peaks based on the one or more estimated molecular weights corresponding to centering the visual representation about the estimated molecular weight; The system according to claim 1 , comprising:

Images