Friday, October 31, 2014

Fwd: FOLLOW-UP re: abstract - Confirmed - Speaking Invitation Clinical Genomics Track this April 21-23 at BioIT World 2015 in Boston


Human Genome Analysis

Identification of noncoding cancer "drivers" from thousands of somatic
alterations is a difficult and unsolved problem. Here, we developed a
computational framework to annotate and prioritize cancer regulatory
mutations. The framework combines an adjustable data context
summarizing large-scale genomics and cancer-relevant datasets with an
efficient variant prioritization pipeline. To prioritize high impact
variants, we developed a weighted scoring scheme to score each
mutation's impact through analyzing conservation, loss-of and gain-of
function events, gene associations, network topology and across-sample
recurrence. Cancer specific information is used to further highlight
potential oncogenic relevant candidates.

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