1:00pm to 2:00pm |
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Computer Science Seminar -Identification of Association Patterns in Public Literature Using Network-based Computational Approaches
(Greater Washington DC Metro Area)
Yuji Zhang, assistant professor in the Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, will present "Identification of Association Patterns in Public Literature Using Network-based Computational Approaches: Case Studies in Vaccine Research."
She will describe the primary contributions she has made to the identification of association patterns in literature-based disease-drug-gene network; knowledge comparison of vaccine-related associations in PubMed abstracts and the Vaccine Ontology; and identification of sex-associated network patterns in Vaccine Adverse Event Reporting System (VAERS).
Zhang received a Ph.D. in computer engineering from Virginia Tech in 2010.
Her research focuses on developing translational bioinformatics and systems biology approaches to understand the physiological states of the cell and the organism, including disease states. Specifically, she has developed various network-based computational approaches to integrate multi-omics data sources for gene regulatory network inference, disease biomarker discovery, disease-drug-gene association analysis, and disease-specific network identification.
Zhang's mission is to leverage the gap between the analytical needs arising from multi-source big data in cancer research and advanced computational approaches.
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