Identifying intragenic functional modules of genomic variations associated with cancer phenotypes by learning representation of association networks

Identifying intragenic functional modules of genomic variations associated with cancer phenotypes by learning representation of association networks

BACKGROUND: Genome-wide Association Studies (GWAS) aims to uncover the link between genomic variation and phenotype. They have been actively applied in cancer biology to investigate associations between variations and cancer phenotypes, such as susceptibility to certain types of cancer and predispos...

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Bibliographic Details
Main Authors:	Agasthya, G. (Author), Danciu, I. (Author), Goethert, I. (Author), Huffman, J.E (Author), Justice, A. (Author), Kim, M. (Author), VA Million Veteran Program (Author)
Format:	Article
Language:	English
Published:	NLM (Medline) 2022
Subjects:	Genome-wide Association Study Machine Learning Network Representation Learning
Online Access:	View Fulltext in Publisher

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