138results about "DNA computers" patented technology

The invention discloses a deep learning-based mixed-shooting image correction method and system, and relates to the field of computer vision, and the method comprises the steps: carrying out the illumination normalization processing of a mixed-shooting image group, and constructing a Gaussian pyramid image group; inputting the Gaussian pyramid image group into a ResNet-34 network to extract a multi-scale feature map, and generating spatial position and channel statistical information; and converting the spatial position and the channel statistical information into a DNA sequence fragment through a DNA base mapping rule. Illumination normalization is achieved through Retinex decomposition and Gaussian filtering, the exposure difference of different devices is effectively eliminated, the input quality of follow-up processing is guaranteed, traditional feature description is converted into biological sequence comparison through DNA base coding, geometric parameters are optimized in combination with quantum annealing, and the accuracy of the method is improved. The matching precision of a low-texture area and the correction effect of a large-view-angle-difference scene are remarkably improved, and the sub-pixel-level matching precision is achieved based on weighted RANSAC and multi-scale pyramid fusion.

The invention discloses a multi-parameter cooperative control method for non-excavation repair of a drainage pipe network in urban updating, and relates to the technical field of municipal engineering, and the method comprises the steps: firstly constructing a quantum entanglement sensing pipe network digital twinborn model, fusing multi-source data, monitoring micro-strain in real time through a nano sensor, deploying a self-organizing intelligent node and terahertz imaging equipment, and constructing a quantum entanglement sensing pipe network digital twinborn model; multi-dimensional features are extracted, repair parameters are dynamically regulated and controlled through technologies such as magnetofluid plugging and multi-robot cooperation based on digital twinning virtual simulation, finally, the repair effect is evaluated and the scheme is optimized in combination with cognitive calculation and microbial self-healing technologies, and full-process intelligent control is achieved. The intelligent level of non-excavation repair of the drainage pipe network is improved, the problem that traditional monitoring is one-sided is solved through high-precision data fusion, precise construction control is achieved through cooperation of magnetofluid leaking stoppage and the robot, durability is enhanced through the microorganism self-healing technology, repair quality and efficiency are improved, and urban updating and sustainable development are promoted.

The present disclosure, among other things, provides machine-learning technologies for identifying and localizing particular genomic elements (e.g., gene elements and / or regulatory elements) within nucleotide sequences, such as DNA and / or RNA sequences. In certain embodiments, similar to the manner in which image processing methods can be used to localize particular objects in images at pixel level resolution, referred to as “segmentation,” systems and methods of the present disclosure predict presence and locations of certain genomic elements within nucleotide sequences, thereby “segmenting” nucleotide sequences. Accordingly, genomic element segmentation technologies described herein may be used to generate annotations that identify and label portions of nucleotide sequences according to their predicted (e.g., via machine learning models described herein) function—e.g., as protein-coding genes, untranslated regions, splice sites, promotors, enhancers, etc. Among other things, these genomic annotations may be used to inform underlying biological processes driving diseases and facilitate development of new therapies.

The invention provides an invasive species identification method and device based on deep learning and DNA storage and electronic equipment, and relates to the technical field of invasive organism prevention and control, and the method comprises the steps: obtaining a to-be-identified invasive species image, and generating a first DNA sequence of a to-be-identified invasive species in the invasive species image through a deoxyribonucleic acid DNA encoder; obtaining a plurality of second DNA sequences to be hybridized from the invasive species database, and obtaining the hybridization yield of the first DNA sequence and each second DNA sequence by using a hybridization yield predictor; and determining the species category corresponding to the DNA sequence with the highest hybridization yield as the species category of the invasive species to be identified. According to the method provided by the invention, the strong feature extraction capability of deep learning is combined with the advantages of ultrahigh density and ultra-long stability of DNA as a data storage medium, so that end-to-end mapping and recognition from a species image to an exclusive DNA sequence thereof are realized.

A cryoelectron microscope density map refinement method based on a mixed attention mechanism belongs to the field of bioinformatics, and comprises the following steps: firstly, constructing a training data set containing an experimental density map and a corresponding atomic structure, extracting feature embedding representation of the atomic structure by using a protein large language model, and generating a corresponding simulated density map according to the atomic structure; cutting each experimental density map and the corresponding simulated density map into blocks; thirdly, the experimental density map blocks and the structural features are embedded and input into a Transform deep learning network based on a mixed attention mechanism, and prediction density map blocks are generated; then calculating a loss difference value between each group of prediction density map blocks and the corresponding simulation density map block, and updating network parameters through a back propagation difference value; and finally, segmenting a to-be-processed cryoelectron microscope density map into a plurality of density map blocks, and predicting and assembling the density map blocks through the trained network to obtain a final refined density map. The method can improve the quality of the density map, and is high in robustness.

The invention provides a Word document processing method and system based on a DNA genetic model, and relates to the technical field of document processing, and the method comprises the following steps: carrying out homogenization determination on two basic Word documents; splitting the document which is judged to be homogeneous into a chain A and a chain B, and performing variation processing on a title block; crossing and recombining to form two sub-documents; and evaluating the sub-documents based on the adaptive function, and adding the sub-documents with evaluation results higher than a threshold value into a resource pool. According to the method, diversified documents are generated by simulating a DNA genetic mechanism, the document generation efficiency is improved, different user requirements are met, and the content creation cost is reduced.

The present invention relates to the field of data storage, and discloses a DNA-based dynamic balancing system, a data storage method, and a decoding method. During the process of encoding the first data to obtain a DNA molecular chain, various constraints are added to the first address and the second address, enabling the encoded data to be read efficiently and accurately. For example, the Hamming distance between the first address and the second address is greater than or equal to half of the length of the first address, reducing the possibility of address selection errors during reading; the prefix of the first address is different from the prefix of the second address and the suffix of the second address, avoiding the possibility of matching errors during the reading process; the content of guanine and cytosine in the prefix of each primer accounts for a preset ratio of the total content of guanine, cytosine, adenine, and thymine contained in the primer, resulting in high accuracy when sequencing is required to read the encoded data in advance.

Compositions, methods, and systems for handling liquids, for example, liquids containing one or more biological substances or chemical reagents, or combinations thereof. The liquid can be an "ink" containing nucleic acids (e.g., DNA) for "nucleic acid "printing" or "writing." These nucleic acids can include one or more components of nucleic acid molecules that encode digital information ("identifiers") that can be used in methods and systems for encoding digital information in nucleic acid. Described in this specification are technologies including an ink supply system and associated ecosystem for a DNA writing device for use with the technologies for encoding, storing, reading, and / or processing digital information in nucleic acid molecules.

Presented herein are writeable polymers (e.g., writeable nucleic acid polymers) and related methods for data storage. In general, writeable polymers (e.g., nucleic acid polymers) contain one or more convertible residues (e.g., convertible nucleic acid bases) that can be converted from a first state to a second state, and the first state and the second state are different. Various methods, such as polymerase extension by rolling circle reaction or chemical synthesis and ligation, can be used to generate writeable nucleic acid polymers. Also presented herein are various methods for writing or encoding into writeable nucleic acid polymers by selectively converting nucleic acid bases to a second state. Also presented herein are various methods for reading or decoding data from encoded nucleic acid polymers.

The present disclosure, among other things, provides machine-learning technologies for identifying and localizing particular genomic elements (e.g., gene elements and / or regulatory elements) within nucleotide sequences, such as DNA and / or RNA sequences. In certain embodiments, similar to the manner in which image processing methods can be used to localize particular objects in images at pixel level resolution, referred to as "segmentation," systems and methods of the present disclosure predict presence and locations of certain genomic elements within nucleotide sequences, thereby "segmenting" nucleotide sequences. Accordingly, genomic element segmentation technologies described herein may be used to generate annotations that identify and label portions of nucleotide sequences according to their predicted (e.g., via machine learning models described herein) function – e.g., as protein-coding genes, untranslated regions, splice sites, promotors, enhancers, etc. Among other things, these genomic annotations may be used to inform underlying biological processes driving diseases and facilitate development of new therapies.

A messenger RNA (mRNA) vaccine has emerged as a promising direction to combat the COVID-19 pandemic. This requires an mRNA sequence that is stable and highly productive in protein expression, features to benefit from greater mRNA secondary structure folding stability and optimal codon usage. Sequence design remains challenging due to the exponentially many synonymous mRNA sequences encoding the same protein. The present disclosure presents embodiments of a linear-time approximation (LinearDesign) reducing the design to an intersection between a Stochastic Context Free Grammar (SCFG) and a Deterministic Finite Automaton (DFA). Embodiments of the LinearDesign may implement an mRNA sequence design using much reduced time with very limited loss. Various methodologies, e.g., finding alternative sequences based on k-best parsing or directly incorporating codon optimality, are presented for incorporating the codon optimality into the design. Embodiments of the LinearDesign may provide efficient computational tools to speed up and improve mRNA vaccine development.

The invention provides a multimodal transport alternative path and transport scheme generation method based on road network node interruption. The method comprises the following steps: acquiring road network interruption information; if the road network interruption information is updated, for each original path, judging whether the original path comprises the road network interruption information or not; if yes, marking a break point in the original path, constructing an upstream candidate loading and unloading point set and a downstream candidate loading and unloading point set based on a first constraint condition, and selecting a loading and unloading node from each of the upstream candidate loading and unloading point set and the downstream candidate loading and unloading point set by adopting an upper-layer model by taking the minimum duration as a first objective function; inputting the selected first loading and unloading node and the selected second loading and unloading node into a lower-layer model, wherein the lower-layer model adopts a genetic algorithm to construct a multimodal transport replacement path set; and when the transportation unit travels to one end of the path, determining a final path based on the consumed time of each path, and constructing a multimodal transportation scheme.

The invention relates to a DNA data storage molecular tag based on nanopores and a preparation method and application thereof, and belongs to the technical field of DNA storage. The molecular tag is prepared by modifying azido polysaccharide onto an alkyne-containing DNA chain through a click chemical reaction. Hybridizing and fixing the molecular tag and a DNA bracket chain containing a specific notch structure, and scanning by using a glass nanopore; when the molecular tag passes through the nanopore, a characteristic ionic current blocking signal is generated, and accordingly data coding is achieved. The molecular tag disclosed by the invention is low in cost and simple and convenient to operate; polysaccharide with wide sources and efficient click chemistry are utilized, so that the preparation cost and complexity are remarkably reduced; the physicochemical properties of polysaccharide molecules are stable, the consistency of read signal amplitudes is ensured, the decoding accuracy is high, the label structure stability is good, and a guarantee is provided for long-term storage of data; based on a reversible hybridization storage structure, data updating can be realized without synthesizing a new DNA chain.

Methods, systems, and devices for encoding data for storage in genetic material are disclosed. For example, a computing system can segment user data into a plurality of data blocks and generate seed data characterizing a plurality of fountain code seeds. Additionally, the computing system can, for each data block, implement a set of operations to generate one or more data packets. In some instances, the set of operations can include, for each of the plurality of fountain code seeds, determining a bit value and a corresponding meta code value, and determining which of the fountain code seeds has a meta code value for the bit value that matches a value for the bit position identified in the metadata. Furthermore, the computing system can, for each data packet, cause implementation of a second set of operations to synthesize a polynucleotide strand from at least the bit values of the corresponding data packet.

Compositions, methods, and systems for handling liquids, for example, liquids containing one or more biological substances or chemical reagents, or combinations thereof. The liquid can be an "ink" containing nucleic acids (e.g., DNA) for "nucleic acid "printing" or "writing." These nucleic acids can include one or more components of nucleic acid molecules that encode digital information ("identifiers") that can be used in methods and systems for encoding digital information in nucleic acid. Described in this specification are technologies including an ink supply system and associated ecosystem for a DNA writing device for use with the technologies for encoding, storing, reading, and / or processing digital information in nucleic acid molecules.

Synthetic molecular tags are placed on an item at various points in a supply chain to create a molecular record of movement through the supply chain. Associations between each unique synthetic molecular tag and individual locations in the supply chain are stored in an electronic record which may be maintained in the cloud. The synthetic molecular tags are collected from the item and sequenced to determine movement of the item through the supply chain by reference to the electronic record. The synthetic molecular tags can be used for identifying recalled items based on locations in the supply chain associated with a recall. The synthetic molecular tags may be polynucleotides such as deoxyribose nucleic acid (DNA). The item may be any type of item including food.

In a method for determining an optimal chemical modification for a base sequence of an RNA therapeutic agent, a base sequence modification module acquires, as learning data, biological properties when a plurality of chemical modifications are applied to a plurality of base sequences. Among the learning data, at least two sequences to which different chemical modifications are applied to the same base sequence are randomly selected and sequentially input into an artificial neural network, and the output values output for each of the at least two input sequences are compared. The process of training the artificial neural network is repeatedly performed so that the artificial neural network outputs a larger value as the biological properties of the input sequence are better, to generate an optimal chemical modification prediction model. Using the optimal chemical modification prediction model, an optimal chemical modification having excellent biological properties when applied to the base sequence of the RNA therapeutic agent is determined among the first to w-th chemical modifications.

Disclosed herein is an RNA editing tool for use in a system designed to measure RNA and manipulate specific cell types in vivo.The RNA sensor system comprises: a) a single-stranded RNA (ssRNA) sensor that comprises a stop codon and a payload, and optionally further comprises a normalization gene; and b) an adenosine deaminase that acts on RNA (ADAR), where the sensor can bind to target ssRNA to form a double-stranded RNA (dsRNA) that is a substrate for ADAR deaminase; the substrate comprises a mismatch within the stop codon; the mismatch can be edited by ADAR deaminase, and the edit can effectively remove the stop codon, allowing the payload to be translated and expressed.Also disclosed is a method for quantifying ribonucleic acid (RNA) levels using the RNA sensor system.

In a method for determining an optimal chemical modification for a nucleotide sequence of an RNA therapeutic, a sequence modification module acquires, as learning data, biological characteristics corresponding to when multiple chemical modifications are applied to multiple nucleotide sequences, creates an optimal chemical modification prediction model by repeatedly performing a process of randomly selecting, among the learning data, at least two sequences in which different chemical modifications are applied to the same nucleotide sequence, sequentially inputting the selected sequences into an artificial neural network, and training the artificial neural network to compare output values for the input sequences and output a higher value as the biological characteristics for the input sequence are better, and uses the model to determine, as an optimal chemical modification, a chemical modification showing the best biological characteristics when applied to the nucleotide sequence of the RNA therapeutic, among first to wth chemical modifications.

This invention involves the self-assembly of DNA molecules with divalent metal ions to obtain DNA / metal nanoparticles; coating the surface of the DNA / metal nanoparticles with a polyelectrolyte layer to obtain DNA / metal@LBL nanoparticles; and growing SiO2 on the surface of the DNA / metal@LBL nanoparticles to obtain stable DNA / Fe@LBL@SiO2 particles. A set of DNA double-stranded molecules with complementary base fragments is used. One base fragment is immobilized on the surface of the DNA / Fe@LBL@SiO2 nanoparticles to form addressable DNA / Fe@LBL@SiO2-ssDNA nanoparticles. The other complementary base fragment is immobilized on the surface of magnetic beads to form trapping magnetic beads. The trapping magnetic beads and the addressing DNA nanoparticles are selected by specific base pairing of base fragment primers, and the downstream hybridization products can be separated magnetically, ultimately achieving the separation objective.

In a method for determining an optimal chemical modification for a nucleotide sequence of an RNA therapeutic, a sequence modification module acquires, as learning data, biological characteristics corresponding to when multiple chemical modifications are applied to multiple nucleotide sequences, creates an optimal chemical modification prediction model by repeatedly performing a process of randomly selecting, among the learning data, at least two sequences in which different chemical modifications are applied to the same nucleotide sequence, sequentially inputting the selected sequences into an artificial neural network, and training the artificial neural network to compare output values for the input sequences and output a higher value as the biological characteristics for the input sequence are better, and uses the model to determine, as an optimal chemical modification, a chemical modification showing the best biological characteristics when applied to the nucleotide sequence of the RNA therapeutic, among first to wth chemical modifications.

The application belongs to the technical field of biological computing, and discloses a ternary addition system and a computing method based on DNA strand displacement, which comprises an input unit, a computing unit and an output unit. The input unit adds the input information to the corresponding computing module. The computing unit comprises nine modules, each of which is provided with a competitive blocking circuit and a carry computing gate, and dynamically selects a result bit 1 or 2 and generates a carry signal. The output unit outputs the digital information of 0-2 according to the fluorescent signal of the result bit, extracts the next bit carry information generated by the carry computation, amplifies the signal and then adds it to the next bit computation. The application breaks through the limitation of the number of DNA computing bits through the cooperation of the ternary gate control architecture and the fuel chain amplification, can accurately calculate the ternary addition, can expand the number of bits calculated, can realize 10-bit addition operation, and can be integrated with the expansion of the multiplication logic, thereby providing a universal framework for the molecular arithmetic unit.

Systems, methods, and apparatus for generating a DNA / gene sequence output, given a protein sequence input. In one aspect, the protein-to-DNA mapping system includes a protein language model (embedder) that generates a high-dimensional protein embedding from a low-dimensional protein sequence input; and the system includes a protein-to-DNA translator that processes the protein embedding and generates a DNA sequence output, based on the protein embedding. The protein-to-DNA translator is a neural network (e.g., a Seq2Seq model) and is configured with translation coefficients that may be trained with a training dataset, comprising the training protein and DNA embeddings. Training the translation coefficients can include supervised learning that maps the protein embedding (input) to a DNA sequence (target). The systems, methods, and apparatus may increase protein yield / expression, improve protein functionality, enhance gene therapy efficacy, streamline synthetic biology design, and / or broaden functional genomics studies, all leading to reduced costs, better performance, and increased accessibility.

Multiplex similarity search can be performed in a DNA data storage context. The described technologies can support a plurality of different DNA data storage queries in a single query run. A linking strand can be used to connect a query to its matching data element. After the query finds a matching data element, a result strand can be sequenced to the reveal the matching data element as well as which of the queries resulted in the match. Thus, in a multiplex similarity search scenario, a plurality of result strands from a single query run can be correlated to a plurality of different queries. Also, the result strand can be of significantly longer length than both the unmatched data strands and the unmatched query strands. Therefore, filtering based on length can provide more accurate results.

Methods, systems, and apparatuses to encode data for storage in genetic materials. For example, a computing system may segment user data into a plurality of data blocks and generate seed data characterizing a plurality of fountain code seeds. Additionally, the computing system may, for each data block, implement a set of operations that generate one or more data packets. In some instances, the set of operations may include, for each of the plurality of fountain code seeds, determining a bit value and corresponding metaCode value and determining which of the fountain code seeds has a metaCode value of the bit value that matches a value of the bit position identified in the metadata. Moreover, the computing system may, for each data packet, cause an implementation of a second set of operations that synthesize a polynucleotide strand in accordance with at least bit values of the corresponding data packet.

The present invention is directed to a single input multiplex decision expression system, and a method of using same, such as for expressing a reporter protein.

The technology disclosed relates to a neural network-based variant pathogenicity classifier for indicating a likelihood that a variant amino acid is benign or pathogenic. The disclosure particularly relates to a computer-implemented method comprising inputting, into a neural network based variant pathogenicity classifier trained to classify a variant amino acid sequence as benign or pathogenic a reference amino acid sequence for a protein; a variant amino acid sequence for the protein comprising a variant amino acid; and a conservation profile representing conservation of amino acids in a reference protein sequence across aligned protein sequences of other species; and generating, as an output of the neural network-based variant pathogenicity classifier, a pathogenicity score indicating a likelihood that the variant amino acid is benign or pathogenic.

Provided are a method and system for storing information using DNA. The method comprises: 1) obtaining a DNA fragment attribute library, wherein the DNA fragment attribute library comprises a plurality of DNA molecules, and comprises a retrieval table of storage object attributes and the DNA molecules, and each DNA molecule comprises double-stranded DNA, which represents the storage object attribute, and a single-stranded sticky end for connection; 2) on the basis of the retrieval table, encoding information to be stored, so that same is directly mapped to a corresponding DNA molecule in the DNA fragment attribute library; 3) acquiring corresponding DNA fragments from the DNA fragment attribute library, and connecting same, so as to obtain a connected DNA molecule; and 4) storing the connected DNA molecule. The method and system can be extended to different data types and different application scenarios, and prevent an oligonucleotide sequence from being repeatedly synthesized during storage, thereby greatly reducing storage cost.

The present disclosure provides a method, a device, and a system for storing information in a molecule. The method includes: obtaining information to be stored, wherein the information to be stored has one or more bit-groups, a position of each bit-group in the information to be stored is represented by a first address, a value of each bit-group is represented by a first content, and each bit-group has one or more bits; determining a molecule module corresponding to at least one bit-group of the one or more bit-groups, wherein the molecule module includes a first molecule module, and the first molecular module is configured to represent both the first address and the first content of a corresponding bit-group; and generating a composition based on the determined molecular module such that the composition corresponds to the information to be stored.

Described herein are systems and methods for quality control of polynucleotides. The provided systems and methods for quality control are performed before, during, or after synthesis or storage of the polynucleotides. Further provided herein are system and methods for performing quality control of a surface, for example for synthesis or storage of polynucleotides.