Automated Identification, Prioritization and Visualization of Large-Scale Genomic Data

Automated Identification, Prioritization and Visualization of Large-Scale Genomic Data

Genomenon’s poster presented at the Association of Molecular Pathologists (AMP) 2015 Annual Meeting.  Automated Identification, Prioritization and Visualization of Large-Scale Genomic Data written by Mark Kiel, Nathan Patel, Richard Peng, Steve Schwartz, Megan Lim and Kojo Elenitoba-Johnson discusses the mining of millions of scientific articles to automate variant curation for NGS tertiary analysis.   This has been the underlying technical focus of Mastermind for the last 3 years.

To date, Mastermind has read 3.3 million full text genomic articles for full coverage of the somatic cancer, hereditary cancer, cardiomyopathy, and infertility literature – and looked for every disease-gene-variant relationship in each and every article.  This is what gives Mastermind the power to quickly find all the literature tied to any gene or variant and return prioritized results to the user within seconds – overcoming the time-consuming, incomplete PubMed and Google searches.

Next on the list for Mastermind to mine is the the scientific literature for the rest of the genetic and rare diseases.

Here’s a link to read the entire poster: genomenon-mastermind-poster.

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