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143 results about "Hypervariable region" patented technology

A hypervariable region (HVR) is a location within nuclear DNA or the D-loop of mitochondrial DNA in which base pairs of nucleotides repeat (in the case of nuclear DNA) or have substitutions (in the case of mitochondrial DNA). Changes or repeats in the hypervariable region are highly polymorphic.

Analysis method for diversity of microbes and abundance of species in coal seam water

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.
Owner:SHANXI JINCHENG ANTHRACITE COAL MINING GRP CO LTD

Plant endophyte 16S rRNA gene amplification method and application

The invention discloses a plant endophyte 16S rRNA gene amplification method and application. The amplification method includes the following steps of plant pretreating; plant-sample total DNA extracting; sample 16S rRNA gene amplifying, wherein sample 16S rRNA gene amplifying comprises 16S rRNA gene total-length emulsion PCR amplifying and 16S rRNA gene hypervariable-region/conserved-region amplifying sub-amplifying; high-throughput sequencing and biological information analyzing based on a Illumina platform, wherein high-throughput sequencing and biological information analyzing based on the Illumina platform comprises plant endophyte 16S rRNA gene amplicon purifying and recycling, amplicon sequencing library establishing, Illumina HiSeq sequencing and sequencing data bioinformatics analysis. The gene amplification method is used for high-throughput-sequencing plant disease detection and phytophagous animal enteric microorganism detection. Sequencing analysis of plant endophytic bacteria is carried out with the high-throughput sequencing technology, the data size is larger, the detection result is more complete, pollution of plant hosts is reduced to the maximum degree, the result multiformity is higher, and the cost is low.
Owner:成都罗宁生物科技有限公司

Method for detecting rhizosphere soil prokaryotic microorganisms of various soybeans based on 16SrDNA deep sequencing

The invention belongs to the technical field of soil microbiology, and in particular relates to a method for detecting rhizosphere soil prokaryotic microorganisms of various soybeans based on 16SrDNA deep sequencing. The method comprises the following steps: 1. collecting root shook-off soil and rhizosphere soil of various soybeans in different development stages; 2. extracting microorganism metagenome DNA from the soil; 3. performing PCR amplification on a 16S rDNA fourth hypervariable region in the DNA by virtue of a dual-tag primer so as to construct a library; 4. simultaneously synthesizing and sequencing the qualified library by virtue of a Illumina Miseq platform in a mode of 250 nucleotides at dual ends, so that pure READS is obtained; 5. splicing: clustering at least 38000 effective tags generated from each sample into an operable classifying unit; 6. conducting significance analysis on species composition, structure, diversity and relative abundance difference; and 7. by taking the root shook-off soil as a control group of the system, accurately determining the composition, structure, diversity and relative abundance of a rhizosphere soil prokaryotic microorganism colony, and comparing the various soybeans.
Owner:NANJING UNIV

Accurate human DNA typing method, reagent and application

The application discloses an accurate human DNA typing method, a reagent and application. According to the accurate human DNA typing method, a short tandem repeat sequence, polynucleotide polymorphicsites covering a whole genome, a mitochondrial DNA hypervariable region I, a mitochondrial DNA hypervariable region II and an Amel enamel gene are detected simultaneously to obtain accurate typing andbase sequences of all the sites, thereby realizing accurate typing of human DNAs. The disclosed method having high resolution ratio is capable of carrying out efficient and accurate individual recognition and has the extremely high individual recognition capacity for difficult detection materials and highly-degraded detection materials; the non-parent exclusion rate is larger than 99.999999% in paternity identification and the accuracy is high; the compatibility is high, the existing individual recognition detection kit can be covered, and the method can be used for analyzing race groups in different regions or countries by combining human genome data. Besides, the method disclosed by the invention is relatively high in adaptability of detection materials and the human DNA extracted by various experimental methods can be detected.
Owner:BGI FORENSIC TECH (SHENZHEN) CO LTD

Deep learning method for predicting binding site on antibody through sequence

ActiveCN112397139AAccurately predict binding sitesImprove interpretabilityNeural architecturesNeural learning methodsAntibody combining siteAlgorithm
The invention relates to the field of antibody binding site prediction, and particularly provides a deep learning method for predicting a binding site on an antibody through a sequence. The method comprises the following steps: acquiring a plurality of hypervariable regions on the antibody, and connecting the plurality of hypervariable regions in series to form a hypervariable region sequence, adding an unknown type of amino acid among different hypervariable region sequences as a distinguishing identifier, wherein the characteristics of each amino acid in the hypervariable region sequence comprise word embedding characteristics and additional characteristics; combining the word embedding features and the additional features to obtain a final feature matrix, and inputting the feature matrix into a neural network model, wherein the neural network model adopts a bidirectional long-short-term memory network and a transformer encoder to learn sequence information of high-variable regions and interaction information between different high-variable regions, and predicts antibody binding sites. According to the invention, the antibody binding site can be accurately predicted by learning the interaction information between different hypervariable regions.
Owner:SUN YAT SEN UNIV
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