alexa Gang Fu | National Institutes of Health
ISSN: 2327-5146

General Medicine: Open Access
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Gang Fu

Gang Fu Gang Fu Staff Scientist NCBI\NLM\NIH 8600 Rockville Pike Bethesda United States

 Dr. Gang Fu did his Pharmaceutical Science and M.S. in Medicinal Chemistry from Peking University Health Science Center, China.He also completed his M.S. in Computer and Information Science and Ph.D. in Pharmaceutical Science from University of Mississippi.He received many awards in academics and also in his career and been honoored with most prestigious Sevice award,Fellow award for research excellence from National Institute of Health.He is a member of American Chemical Society and also a member of American Association of Pharmaceutical Scientists.

Research Interest
My research interests focus on applying the machine learning algorithms, text-mining approaches, and ontological reasoning on “omics” big data for knowledge discovery in life science domain. Knowledge discovery can be transformed as link prediction problem in the biological/biomedical networks, comprising drugs, genes, diseases, and other biomedical concepts. Bio-ontologies encodes domain specific knowledge base using description logic, which enables reasoning and rule-based inference to discover new knowledge based on the existing ones. Machine learning algorithms including decision tree, random forest, support vector machine, and deep learning may study the rule sets from bio-ontologies to provide insights on ranking and clustering to support decision making. In addition, the co-occurrence based text-mining approaches can be applied on chemical/gene/disease and biomedical literature associations to further validate and compare the ranking and clustering results.
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