Researchers at the University of Illinois at Urbana-Champaign (UIUC) and the Mayo Clinic computationally harnessed single-nucleotide polymorphisms (SNPs) to identify disease pathways.
The Variant Set Annotator (VarSAn) tool utilizes disease-related SNPs to forecast which pathways they may disrupt.
UIUC's Saurabh Sinha said, "The underlying computation is similar to how Google uses an algorithm to identify the right Web pages for searches. These types of algorithms are applicable in biology as well to understand genetic variation."
Explained UIUC's Xiaoman Xie, the researchers validated the VarSAn tool through a literature search and an objective technique that tested the consistency of its findings.
Sinha said the work was part of the Mayo Grand Challenge to enhance understanding of Hypoplastic Left Heart Syndrome, a congenital pediatric heart disorder.
From University of Illinois Institute for Genomic Biology
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Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA
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