Wednesday, April 12, 2017

Qin lab brief description

Dr. Hong Qin's group uses computational and mathematical approaches to investigate biomedical and biological questions.  One focus is to develop probabilistic gene network models to infer network changes during cellular aging. We build gene network models from heterogenous genomics data sets, including protein interactions, gene expression data sets, RNAseq data sets, protein mass-spec data sets, high-throuput phenotypic screens, and gene annotations.  We are developing machine-learning methods to automatically estimate cellular lifespan from time-lapsed images. We are also applying engineering principles to study molecular, biological, and ecological networks. We are developing deep-learning methods for better classification and prediction using heterogenous biomedical and biological large data sets. Dr. Hong Qin is a recipient of a NSF CAREER award 2015-2020.

Qin's expertise: Graph reliability modeling; Bioinformatics; Computational genomics; Mathematical modeling; Systems Biology;  Cellular aging; Gene network analysis and modeling. 

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