Dr. Feng's works focus on cancer related translational studies (“from bench to bed”) by means of algorithm development and analysis of high-throughput “-omic” data, such as next-generation sequencing, microarray data, ht-qPCR data, as well as pipeline integration for biomarker identification, variant detection, drug discovery and repositioning, by combining varies of tools (developed in-house or third party) and datasets including clinical data, genomic data, etc., with annotations, like functions, pathways, diseases, compounds, and so on. I am also interested in molecular modeling, such as molecular dynamics simulation, coarse grain simulation, monte carlo simulation, etc., which is also widely applied in compounds screening at atomic level. Furthermore, as the executive director of the bioinformatics consulting core, I also lead an active team to provide professional services for researchers from universities, hospitals and companies with our expertise on biomedical informatics.
Selected Peer-reviewed publications:
Feng G, Shaw P, Rosen ST, Lin SM and Kibbe WA, “Using the Bioconductor GeneAnswers Package to Interpret Gene Lists.” Methods Mol Biol. 2012 802:101-12.
Mei H, Xia T, Feng G, Zhu J, Lin SM and Qiu Y, Opportunities in Systems Biology to Discover Mechanisms and Repurpose Drugs for CNS Diseases, Drug Discovery Today, 2012 Jun 30.
Feng G, Hobbs J, Lu X, Hou L, Jiang H, Baccarelli A, Chandler J, Kibbe WA, Du P and Lin SM, “A Statistical Method to Estimate DNA Copy Number from Illumina High density Methylation Arrays”, BMC Proceeding, 2012 (Accepted)
Feng, G, Du, P., Krett, N.L., Tessel, M., Rosen, S., Kibbe, W.A. and Lin, S.M. (2010) A collection of bioconductor methods to visualize gene-list annotations, BMC Research Notes, 3,10.
Du P, Feng G (Co-1st Authors), Flatow J, Song J, Holko M, Kibbe WA and Lin SM, From disease ontology to disease-ontology lite: statistical methods to adapt a general-purpose ontology for the test of gene-ontology associations. Bioinformatics. 2009 Jun 15;25(12):i63-8.