Mining Genomic Literature for Variant Interpretation and Gene Panel Design

How the Mastermind Genomic Search Engine helped clinicians from University of Vermont and researchers from Q2 Solutions

Watch an expert panel discuss how they used the new Mastermind Genomic Search Engine to mine the full text of the genomic literature for two key applications: variant interpretation and the development of evidence-based diagnostic gene panels.

Summary:

Mark Kiel, Founder and Chief Scientific Officer of Genomenon, gives an overview of the Mastermind Genomic Search Engine and discusses a comprehensive, evidence-based cancer panel that was produced using automated machine learning techniques. The pan-hematopoietic cancer panel is a comprehensive cancer panel of more than 300 genes supported by specific literature citations from among millions of research publications.

Nikoletta Sidiropoulos and David Seward from the University of Vermont College of Medicine demonstrate their approach and the tools used to quickly and thoroughly mine the scientific literature to interpret variants in somatic cancer cases.

Victor Weigman from Q2 Solutions presents an evidence-based method that his team used to select the content for gene panels by mining millions of full-text genomic articles to identify disease-gene-variant associations. Dr. Weigman explains how he created an evidence-based gene panel in under a week with prioritized literature citations for each biomarker.

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