Neural network architectures for linking biological sequence variants based on molecular phenotype, and systems and methods therefor

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United States of America Patent

PATENT NO 11183271
APP PUB NO 20180165412A1
SERIAL NO

15841106

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Abstract

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We describe a system and a method that ascertains the strengths of links between pairs of biological sequence variants, by determining numerical link distances that measure the similarity of the molecular phenotypes of the variants. The link distances may be used to associate knowledge about labeled variants to other variants and to prioritize the other variants for subsequent analysis or interpretation. The molecular phenotypes are determined using a neural network, called a molecular phenotype neural network, and may include numerical or descriptive attributes, such as those describing protein-DNA interactions, protein-RNA interactions, protein-protein interactions, splicing patterns, polyadenylation patterns, and microRNA-RNA interactions. Linked genetic variants may be used to ascertain pathogenicity in genetic testing, to identify drug targets, to identify patients that respond similarly to a drug, to ascertain health risks, or to connect patients that have similar molecular phenotypes.

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Patent OwnerAddress
DEEP GENOMICS INCORPORATED661 UNIVERSITY AVENUE SUITE 480 TORONTO ON M5G 1M1

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Delong, Andrew Toronto, CA 7 70
Frey, Brendan Toronto, CA 16 216

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