Leveraging Network Biology to Drive Drug Discovery is the first of a two-part series exploring the Computational Biology Methods for Drug Discovery (CBDD), a consortium of pharmaceutical companies focused on implementing state-of-the-art approaches for network and pathway analysis of OMICs datasets to help accelerate innovation. This first class of the series provides an overview of the impact and benefits of the CBDD consortium and how pharmaceutical companies are leveraging network and pathway algorithms to understand disease mechanisms and drive drug discovery. Participants will learn how systems biology tools that combine data with prior knowledge uncover insights from WGS, GWAS, RNA-Seq, and single cell data; how algorithms developed in the consortium can help advance cutting-edge research; and which algorithms are optimal depending on research goal(s). Register separately for Part 2 of this series, Bioinformatics Use Cases.
Computational Biology Methods for Drug Discovery (CBDD) Series: Part 1
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