650 results about "Natural abundance" patented technology

Disclosed are methods for identifying nucleic acid sequences which are of different abundances in different nucleic acid source populations, e.g. differentially expressed genes or genomic variations among individuals or populations of individuals. In one embodiment, probes derived from the source nucleic acid populations are derivatized with a terminal sample ID (SID) sequence characteristic of that population. Upon competitive hybridization of the probes to a reference or index nucleic acid library containing all the sequences in the populations being compared, the SID tags remain single stranded, and those from the different sources are then annealed to one another. Unhybridized (remainder) SID sequences are then quantified. By labeling such remainder SID sequences with a fluorescent dye, FACS sorting of beads containing the hybridized probes can be carried out. The signal ratio upon which such sorting is based is enhanced compared to competitive hybridization using labeled probes without SID sequences.

The present invention provides a method for identifying one or more low abundance sequences differing by one or more single-base changes, insertions, or deletions, from a high abundance sequence in a plurality of target nucleotide sequences. The high abundance wild-type sequence is selectively removed using high fidelity polymerase chain reaction analog conversion, facilitated by optimal buffer conditions, to create a restriction endonuclease site in the high abundance wild-type gene, but not in the low abundance mutant gene. This allows for digestion of the high abundance DNA. Subsequently the low abundant mutant DNA is amplified and detected by the ligase detection reaction assay. The present invention also relates to a kit for carrying out this procedure.

The invention provides a method for analyzing remaining oil distribution of a fractured-vuggy reservoir, belonging to the fields of numerical reservoir simulation and oil-gas field development. In the method, a complex medium consisting of a cave medium, a crack medium and a pore medium is partitioned into a plurality of space unit blocks in a space field; each block consists of V, F and M units which represent a cave, a crack and a substrate in the block respectively and constitute a V-F-M model; the flow of a multi-phase fluid in the complex medium is described by the motion of a fluid among the units in each block and the motion of a fluid among the units of different blocks; and the flow of the fluid among the units can be considered as infiltration flow, pipe flow or laminar flow between parallel walls, Darcy flow or non-Darcy flow. According to the method, scientific description and accurate numerical simulation of the fractured-vuggy reservoir are realized, and technical foundations are laid for the alignment of the remaining oil distribution position of the fractured-vuggy reservoir with a numerical simulation technology, quantitative determination of the reserves abundance of the reservoir, scientific and reasonable development of oil fields provided with the reservoir and final increase in the recovery ratio.

A method and system for quantifying the relative abundance of gene transcripts in a biological sample. One embodiment of the method generates high-throughput sequence-specific analysis of multiple RNAs or their corresponding cDNAs (gene transcript imaging analysis). Another embodiment of the method produces a gene transcript imaging analysis by the use of high-throughput CDNA sequence analysis. In addition, the gene transcript imaging can be used to detect or diagnose a particular biological state, disease, or condition which is correlated to the relative abundance of gene transcripts in a given cell or population of cells. The invention provides a method for comparing the gene transcript image analysis from two or more different biological samples in order to distinguish between the two samples and identify one or more genes which are differentially expressed between the two samples.

Analytical methods and devices are disclosed for separating low abundance analytes by electrophoretically driving the analytes through a sieving matrix to first remove high molecular weight species. Subsequently the remaining low abundance analytes are electrophoretically focused onto a capture membrane where the analytes become bound within a small capture site. After this step the capture membrane may be allowed to dry and then attached to a conductive MALDI sample plate.

The invention discloses a method for detecting mutation information in a multiplex amplification sequencing product of a genome. The method comprises steps as follows: sequencing data are subjected to quality assessment and preprocessing; a recognizable sequencing sequence is selected for sequence assembling; the recognizable sequencing sequence or a sequence obtained through assembling is compared with a reference gene sequence, and preliminary variation information is obtained; fine calibration of sequence variation is performed according to different types of conditions; a calibrated sequencing fragment is obtained; the homozygosis or heterozygosis state of a target fragment is obtained according to the type of the sequencing fragment with the highest abundance; finally, the mutation information in the multiplex amplification sequencing product of the genome is obtained. By means of the method, the amplification product can be rapidly, efficiently and accurately recognized, and the calculation resources are saved; the sequence assembling process is compatible, and the problem of reduction of the quality value of basic groups produced in the sequencing process can be effectively solved; the homozygosis/heterozygosis state of variation information can be more effectively and stably judged, and random errors introduced in the PCR (polymerase chain reaction) process and the sequencing process are eliminated.

A hyperspectral image sparse unmixing method based on random projection includes the following four main steps: (1) data are read by a computer under the environment of MATLAB R2008b; (2) the hyperspectral image data and the hyperspectral library data are randomly projected by the computer; (3) a target function for sparse unmixing is constructed, and the split Bregman algorithm is used for optimizing the target function and working out an extremum until reaching convergence and stopping conditions; (4) an appropriate threshold value is set to process a abundance fraction matrix, so that a final abundance fraction graph and end members can be obtained. The hyperspectral image sparse unmixing method based on random projection utilizes a hyperspectral database to choose the end members, and overcomes the defect that the end members worked out by the conventional algorithm cannot strictly correspond to the spectra of pure materials in the standard hyperspectral database; and moreover, the hyperspectral image sparse unmixing method based on random projection uses the random projection technology to carry out dimensionality reduction on raw data, thus achieving the effects of saving memories and reducing the calculation load. The hyperspectral image sparse unmixing method based on random projection realizes rapid quantitative analysis on hyperspectral images, and has practical value and a broad application prospect in the field of hyperspectral remote sensing image analysis.

A fast and rigorous multivariate curve resolution (MCR) algorithm is applied to remotely sensed spectral data. The algorithm is applicable in the solar-reflective spectral region, comprising the visible to the shortwave infrared (ranging from approximately 0.4 to 2.5 μm), midwave infrared, and thermal emission spectral region, comprising the thermal infrared (ranging from approximately 8 to 15 μm). For example, employing minimal a priori knowledge, notably non-negativity constraints on the extracted endmember profiles and a constant abundance constraint for the atmospheric upwelling component, MCR can be used to successfully compensate thermal infrared hyperspectral images for atmospheric upwelling and, thereby, transmittance effects. Further, MCR can accurately estimate the relative spectral absorption coefficients and thermal contrast distribution of a gas plume component near the minimum detectable quantity.

A method of imaging mass spectroscopy and a corresponding apparatus are provided, wherein the m/z-ratio of ions as well as the location of said ions on a sample surface are detected simultaneously in a time of flight mass spectrometer. The detector is a semiconductor array detector comprising pixels, that each can be arranged to measure a signal intensity of a signal induced by the ions or their time of arrival. A four-dimensional image consisting of the two lateral dimensions on the sample surface, the m/z-ratio representing the ion type and the abundance of an ion type on the surface can be reconstructed from repeated measurements for which a correspondingly adapted computer program product can be involved.

Methods, computer program products and systems for identifying cellular constituents in a secondary tissue that serve as surrogate markers for a target gene expressed in a primary tissue of a species are provided. A classifier is constructed using cellular constituent abundances of cellular constituents in a first plurality of cellular constituents measured in the secondary tissue in a population. This population comprises a first and second subgroup. The classifier is based on a second plurality of cellular constituents that comprises all or a portion of the first plurality of cellular constituents. Abundance levels of each cellular constituent in the second plurality of cellular constituents varies between the first and second subgroup. All or portion of the population is classified into a plurality of subtypes using the classifier. Then, one or more cellular constituents that can discriminate members of the population between a first subtype and a second subtype in the plurality of subtypes are identified.

The invention discloses a controllable and universal directional surface printing method. The method comprises the steps as follows: template glucoprotein is anchored on the surface of a substitution boric acid functional substrate material via boron affinity interaction, the polymer formed by auto-polymerization in water phase of a compound capable of automatically polymerizing forms a printing layer, and a template is eluted under the acid condition to form a printing hollow cavity, as a result, the molecular printing polymer is obtained. The molecular printing polymer prepared via the method not only has the advantages of good specificity, high combination capacity, strong anti-interference capability, quick combination and analysis speed and the like, but also can exclusively identify the template glucoprotein with or without the boron affinity interaction, is adjustable in force of combination with the template when keeping the specificity, and is wide in application range. The method has the advantages of convenience, controllability, universality, high printing efficiency and the like. The molecular printing polymer can exclusively identify, gather, separate and detect the glucoprotein with low enrichment in a complex practical sample.

The invention relates to a risk-constrained oil and gas resource spatial distribution forecasting method which comprises the following steps of: (1) integrating seismic information and geologic information; (2) forecasting the exploration risk probability of a entire region; (3) establishing a resource abundance diagram of the discovered oil and gas accumulation; (4) establishing a resource abundance amplitude diagram and a resource abundance phase diagram; (5) establishing a modified resource abundance amplitude diagram; (6) establishing a risk probability amplitude diagram and a risk probability phase diagram; (7) establishing a forecast oil and gas resource abundance distribution diagram of the entire region; and (8) calculating the resource quantities of different risk regions: excluding the oil and gas accumulation with low abundance; excluding grid data points with high exploration risk; and verifying and modifying according to the data of the explored wells. The method can forecast the resource quantities in different risk regions and the spatial distribution positions of the remained oil and gas resources. A forecasting model and the method have strong operability. The invention can enhance the drilling decision level and the oil and gas exploration efficiency.

The invention belongs to the field of research on microbes in stratum water and provides an analysis method for diversity of microbes and abundance of species in coal seam water to overcome the problems that research on diversity of microbes in an environment has great limitation, species with low abundance in a sample cannot be effectively detected, species with high similarity in the sample are difficult to distinguish, only a minority of microbe species in the sample can be revealed, etc. The method comprises the following steps: acquisition of a coal seam water sample; enrichment of microbial thalli in the water sample and extraction of total DNA of the microbial thalli; amplification of the hypervariable region of 16SrDNA with specific primers; sequencing analysis with an Illumina sequencing platform; and processing of original data of sequencing so as to obtain diversity and abundance of microbes in the water sample. The method can effectively detect species with low abundance in the sample, identifies more than 400 genuses of bacteria in coal seam water, has obvious superiority in research on species and abundance of microbes in coal seam water and is applicable to analysis of diversity of microbes and abundance of species in environments like coal seams and oil gas or shale gas strata.

The present invention relates to a method of diagnosing a renal disorder. The method includes the steps of: (1) obtaining a biological sample from a subject; and (2) determining, in the biological sample, a level of one or more proteins whose abundance in urine change due to the renal disorder, wherein an increase or decrease in the level of one or more of the proteins compared to a control level is indicative of a renal disorder.

Capture particles for harvesting analytes from solution and methods for using them are described. The capture particles are made up of a polymeric matrix having pore size that allows for the analytes to enter the capture particles. The pore size of the capture particles are changeable upon application of a stimulus to the particles, allowing the pore size of the particles to be changed so that analytes of interest remain sequestered inside the particles. The polymeric matrix of the capture particles are made of co-polymeric materials having a structural monomer and an affinity monomer, the affinity monomer having properties that attract the analyte to the capture particle. The capture particles may be used to isolate and identify analytes present in a mixture. They may also be used to protect analytes which are typically subject to degradation upon harvesting and to concentrate low an analyte in low abundance in a fluid.

Mass spectrometry is used to identify a protein of interest. The protein is first ionized then fragmented into protein product ion. Masses of the observed product ions are compared to product ion masses calculated in silico for database protein sequences to identify product ion matches within a predetermined mass tolerance. An algorithm that weights the product ion to matches based upon one or more factors such as product ion abundance, favored cleavage sites, product ion type, precursor ion charge state and polarity is used to score the possible matches to database proteins in order to identify the protein of interest. The invention represents a “top down” approach and is particularly well-suited for identification of a protein in a complex mixture.

The invention belongs to the technical field of remote sensing image processing, in particular to a hyperspectral remote sensing image mixed pixel decomposition method based on independent component analysis. According to the physical characteristics of hyperspectral images, the invention introduces abundance sum-to-one constraint and abundance nonnegative constraint into the target function of independent component analysis, and provides a self-adapting abundance modeling method to describe probability distribution of data, thus presenting favorable applicability towards different remote data. The method can effectively solve the problems of high mixing degree and remote sensing data mixed pixel decomposition under various interferences, and has significant application value in high-precision ground feature classification and detection and recognition of ground targets based on multispectral and hyperspectral remote images.