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Ting Gong, Ph. D.

Present Title & Affiliation

Primary Appointment

Assistant Professor, Dept. of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX

Research Interests

My primary research interest is to develop, optimize and apply novel computational and statistical methods for integrated analyses of versatile existing or emerging high-dimensional data platforms, with the long term goal to derive solutions that may lead to discovery of novel biology insights and impact on genomic research.  I have utilized rigorous statistical methods combined with biologically meaningful algorithms to investigate implicit and explicit biomarkers and biological signatures, and to model the biological pathways and networks associated with disease progression and drug response. Specifically, next generation sequence (NGS) data has revealed unprecedented levels of complexity in biological samples that escaped detection by other "omics" technologies, such as detection and measurement of exons, splice variants, rare transcripts, microRNAs, and SNPs etc. I am also working on several cutting-edge bioinformatics problems in the context of large-scale next-generation genome sequencing projects. A few ongoing projects included reliable signal extraction and deconvolution of complex samples from RNA-Seqdata to understand cellular heterogeneity; integrative analysis of data generated by multiple platforms, such as gene expression, methylation, copy number variation, etc. for statistical inference of gene regulatory networks in important cellular processes. In pursuing scientific discoveries in bioinformatics arena, I enjoyed close collaborations with biologists.

Office Address

Email: tgong@mdanderson.org

Education & Training

Degree-Granting Education

2009 Virginia Polytechnic Institute and State University, Blacksburg, VA, PHD, Electrical and Computer Engineering
2001 Southeast University, Nanjing, China, MS, Biomedical Engineering
1998 Southeast University, Nanjing, China, BS, Biomedical Engineering

Postgraduate Training

2/2010-10/2012 Presidential Postdoctoral Fellow, Biomarker Development/Bioinformatics in Translational Medicine Dept., Novartis Institutes of Biomedical Research, Cambridge, MA

Selected Publications

Peer-Reviewed Original Research Articles

1. Wang N, Gong T, Clarke R, Chen L, Shih IM, Zhang Z, Levine DA, Xuan J, Wang Y. UNDO: a Bioconductor R package for unsupervised deconvolution of mixed gene expressions in tumor samples. Bioinformatics. e-Pub 9/10/2014. PMID: 25212756.
2. Gong T, Szustakowski JD. DeconRNASeq: A Statistical Framework for Deconvolution of Heterogeneous Tissue Samples Based on mRNA-Seq data. Bioinformatics. e-Pub 2/2013. PMID: 23428642.
3. Gong T, Xuan J, Chen L, Riggins RB, Li H, Hoffman EP, Clarke R, Wang Y. Motif-guided Sparse Decomposition of Gene Expression Data for Regulatory Module Identification. BMC Bioinformatics 12(12):82, 2011. e-Pub 3/22/2011. PMCID: PMC3072956.
4. Gong T, Hartmann N, Kohane IS, Brinkmann V, Staedtler F, Letzkus M, Bongiovanni S, Szustakowski JD. Optimal Deconvolution of Transcriptional Profiling Data Using Quadratic Programming with Application to Complex Clinical Blood Samples. PLoS One 6(11):e27156, 2011. e-Pub 11/16/2011. PMCID: PMC3217948.
5. Riggins RB, Lan J, Lan J P-J, Klimach U, Zwart A, Cavalli LR, Haddad BR, Chen L, Gong T, Xuan J, Ethier SP and Clarke R. ERR Mediates Tamoxifen Resistance in Novel Models of Invasive Lobular Breast Cancer. Cancer Research 68(21):8908-8917, 2008.
6. Gong T, Xuan J, Wang C, Li H, Hoffman E, Clarke R, Wang Y. Gene Module Identification from Microarray Data Using Nonnegative Independent Component Analysis. Gene Regul Syst Bio 1(1):349-363, 2007. e-Pub 1/15/2008. PMCID: PMC2759148.

Manuals, Teaching Aids, Other Teaching Publications

1. Gong T and Szustakowski JD. DeconRNASeq Software, 2012.

Last updated: 6/20/2014