Mining Knowledge Graph for Drug Discovery
KGC 2020
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22m
2020 Talk: Knowledge Graph for Drug Discovery: A critical barrier in current drug discovery is the inability to utilize public datasets in an integrated fashion to fully understand the actions of drugs and chemical compounds on biological systems. There is a need to intelligently integrate heterogeneous datasets pertaining to compounds, drugs, targets, genes, diseases, and drug side effects now available to enable effective network data mining algorithms to extract important biological relationships. In this talk, we demonstrate the semantic integration of 25 different databases and develop various mining and predication methods to identify hidden associations that could provide valuable directions for further exploration at the experimental level. (Conflict of Interest: I am the co-founder of Data2Discovery - https://www.d2discovery.com/)
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