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• W1879234420 abstract "Genome-wide association (GWA) studies have identified thousands of genetic variants that contribute to disease and pharmacologic traits. More recently, high-throughput sequencing studies promise to provide a more complete catalog of genetic variants with roles in human phenotypic variation. Yet, characterizing the influence of functional variants on genes, RNAs, proteins, and ultimately disease or pharmacologic traits is a critical challenge for a vast majority of the implicated susceptibility loci. Here we describe SCAN, a bioinformatics resource we have developed to elucidate the functional consequences of genetic variants identified by genome-wide scans. In particular, this public resource implements a systems biology approach to pharmacogenomic discovery." @default.
• W1879234420 created "2016-06-24" @default.
• W1879234420 creator A5036388273 @default.
• W1879234420 creator A5090067435 @default.
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• W1879234420 date "2013-01-01" @default.
• W1879234420 modified "2023-10-16" @default.
• W1879234420 title "SCAN: A Systems Biology Approach to Pharmacogenomic Discovery" @default.
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• W1879234420 doi "https://doi.org/10.1007/978-1-62703-435-7_14" @default.
• W1879234420 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4032625" @default.
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• W1879234420 hasPublicationYear "2013" @default.
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