Zhidong Tu, PhD
- ASSISTANT PROFESSOR | Genetics and Genomic Sciences
Research Topics:Aging, Alzheimer's Disease, Bioinformatics, Computational Biology, Diabetes, Gene Expressions
Zhidong Tu works on developing systems approaches to study disease networks. By integrating large scale genomic and genetic information, he has worked on various problems including signaling pathway inference, drug target gene discovery, and biomarker identification. Dr. Tu received his PhD from Computational Biology program at University of Southern California. He then worked in the Genetics group at Rosetta Inpharmatics, a subsidiary of Merck & Co., Inc to study network of genes whose perturbation lead to type 2 diabetes. He later moved to Merck Boston site to work on cancer drug discovery, where the goal was to combine gene expression, sequence variation, drug response, drug-drug interaction to identify most effective medicine for cancer patients.
Please visit group webpages for more information.
Multi-Disciplinary Training AreaGenetics and Genomic Sciences [GGS]
BS, Fudan University
MS, University of Alabama at Birmingham
PhD, University of Southern California
Systems biology for disease network study
Integrating and interpreting large scale genetic and genomic data turned out to be a promising approach towards understanding complex disease system. One large goal is to develop novel methods that stitch together various pieces of information to identify the network of genes whose perturbation by genetic variation would lead to disease phenotype. Multiple problems need better solutions:
-Better computational models for data-driven disease network discovery
-Mechanistic interpretation of the link between disease network and phenotype changes
-Systems strategy on disease network rectification and translational research
Petralia F, Song WM, Tu Z, Wang P. A new method for joint network analysis reveals common and different co-expression patterns among genes and proteins in breast cancer. Journal of proteome research 2016 Jan;.
Yang J, Huang T, Petralia F, Long Q, Zhang B, Argmann C, Zhao Y, Mobbs CV, G, Schadt EE, Zhu J, Tu Z. Synchronized age-related gene expression changes across multiple tissues in human and the link to complex diseases. Scientific reports 2015; 5.
Petralia F, Wang P, Yang J, Tu Z. Integrative random forest for gene regulatory network inference. Bioinformatics (Oxford, England) 2015 Jun; 31(12).
G. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science (New York, N.Y.) 2015 May; 348(6235).
Yoo S, Takikawa S, Geraghty P, Argmann C, Campbell J, Lin L, Huang T, Tu Z, Foronjy RF, Feronjy R, Spira A, Schadt EE, Powell CA, Zhu J. Integrative analysis of DNA methylation and gene expression data identifies EPAS1 as a key regulator of COPD. PLoS genetics 2015 Jan; 11(1).
Wei Y, Peng S, Wu M, Sachidanandam R, Tu Z, Zhang S, Falce C, Sobie EA, Lebeche D, Zhao Y. Multifaceted roles of miR-1s in repressing the fetal gene program in the heart. Cell research 2014 Mar; 24(3).
The Genotype-Tissue Expression (GTEx) project. Nature genetics 2013 Jun; 45(6).
Tu Z, Keller MP, Zhang C, Rabaglia ME, Greenawalt DM, Yang X, Wang IM, Dai H, Bruss MD, Lum PY, Zhou YP, Kemp DM, Kendziorski C, Yandell BS, Attie AD, Schadt EE, Zhu J. Integrative analysis of a cross-Loci regulation network identifies app as a gene regulating insulin secretion from pancreatic islets. PLoS genetics 2012 Dec; 8(12).
Zhu J, Sova P, Xu Q, Dombek KM, Xu EY, Vu H, Tu Z, Brem RB, Bumgarner RE, Schadt EE. Stitching together Multiple Data Dimensions Reveals Interacting Metabolomic and Transcriptomic Networks That Modulate Cell Regulation. PLoS biology 2012 Apr; 10(4).
Tu Z, Argmann C, Wong KK, Mitnaul LJ, Edwards S, Sach IC, Zhu J, Schadt EE. Integrating siRNA and protein-protein interaction data to identify an expanded insulin signaling network. Genome research 2009 Jun; 19(6).
Wang L, Tu Z, Sun F. A network-based integrative approach to prioritize reliable hits from multiple genome-wide RNAi screens in Drosophila. BMC genomics 2009; 10.
Tu Z, Wang L, Arbeitman MN, Chen T, Sun F. An integrative approach for causal gene identification and gene regulatory pathway inference. Bioinformatics (Oxford, England) 2006 Jul; 22(14).
Jiang R, Tu Z, Chen T, Sun F. Network motif identification in stochastic networks. Proceedings of the National Academy of Sciences of the United States of America 2006 Jun; 103(25).
Tu Z, Wang L, Xu M, Zhou X, Chen T, Sun F. Further understanding human disease genes by comparing with housekeeping genes and other genes. BMC genomics 2006; 7.