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74 results about "Structural variant" patented technology

Structural variation (also genomic structural variation) is the variation in structure of an organism's chromosome. It consists of many kinds of variation in the genome of one species, and usually includes microscopic and submicroscopic types, such as deletions, duplications, copy-number variants, insertions, inversions and translocations.

Systems and methods for clonal replication and amplification of nucleic acid molecules for genomic and therapeutic applications

The present invention provides for methods, reagents, apparatuses, and systems for the replication or amplification of nucleic acid molecules from biological samples. In one embodiment of the invention, the nucleic molecules are isolated from the sample, and subjected to fragmenting and joining using ligating agents of one or more hairpin structures to each end of the fragmented nucleic molecules to form one or more dumbbell templates. The one or more dumbbell templates are contacted with at least one substantially complementary primer attached to a substrate, and subjected to rolling circle replication or rolling circle amplification. The resulting replicated dumbbell templates or amplified dumbbell templates are used in numerous genomic applications, including whole genome de novo sequencing; sequence variant detection, structural variant detection, determining the phase of molecular haplotypes, molecular counting for aneuploidy detection; targeted sequencing of gene panels, whole exome, or chromosomal regions for sequence variant detection, structural variant detection, determining the phase of molecular haplotypes and/or molecular counting for aneuploidy detection; study of nucleic acid-nucleic acid binding interactions, nucleic acid-protein binding interactions, and nucleic acid molecule expression arrays; and testing of the effects of small molecule inhibitors or activators or nucleic acid therapeutics.
Owner:REDVAULT BIOSCI

Systems and methods for clonal replication and amplification of nucleic acid molecules for genomic and therapeutic applications

The present invention provides for methods, reagents, apparatuses, and systems for the replication or amplification of nucleic acid molecules from biological samples. In one embodiment of the invention, the nucleic molecules are isolated from the sample, and subjected to fragmenting and joining using ligating agents of one or more hairpin structures to each end of the fragmented nucleic molecules to form one or more dumbbell templates. The one or more dumbbell templates are contacted with at least one substantially complementary primer attached to a substrate, and subjected to rolling circle replication or rolling circle amplification. The resulting replicated dumbbell templates or amplified dumbbell templates are used in numerous genomic applications, including whole genome de novo sequencing; sequence variant detection, structural variant detection, determining the phase of molecular haplotypes, molecular counting for aneuploidy detection; targeted sequencing of gene panels, whole exome, or chromosomal regions for sequence variant detection, structural variant detection, determining the phase of molecular haplotypes and / or molecular counting for aneuploidy detection; study of nucleic acid - nucleic acid binding interactions, nucleic acid - protein binding interactions, and nucleic acid molecule expression arrays; and testing of the effects of small molecule inhibitors or activators or nucleic acid therapeutics.
Owner:REDVAULT BIOSCI

Model-independent genome structure variation detection system and method

The invention provides a model-independent genome structure variation detection system and method, wherein a model-independent structure variation detection theory is used as a core, and structure variation detection without depending on any variation model is achieved through a variation signal extraction module, a frequent maximum subgraph mining module and a classification module. According tothe system, a frequent variation pattern mining module is used for capturing the characteristics of structural variation left on a genome, and judging a potential structural variation region only by mining abnormal points in a large amount of normal data; and according to different genome disturbance modes of different variation types, different arrangement sequences of variation signals are further caused, and the different variation types are classified on the basis of the different arrangement sequences in combination with a deep learning model with a memory function. According to the invention, the system does not depend on any variation model, so that the variation detection sensitivity and error rate are greatly reduced; and the system is suitable for detection of complex variation types, and an additional structural variation model does not need to be established.
Owner:XI AN JIAOTONG UNIV
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