Biomedical Research Education & Training
Faculty Member

Zhang, Bing, Ph.D.
Associate Professor of Biomedical Informatics

Lab Url:

Phone Number: (615) 936-0090

Email Address:

Zhang, Bing's picture
Academic history
B.S., Nanjing University
M.S., Nanjing University
Ph.D., Shanghai Institute of Plant Physiology, Chinese Academy of Sciences

Office Address   Mailing Address

2525 West End Ave, Room 14123

Suite 1475, 2525 West End Ave 37203

Research Keywords
bioinformatics, systems biology, functional genomics, RNA-Seq, proteomics, data integration, data mining, data visualization, network analysis, cancer

Research Specialty
Network medicine, proteogenomics, democratization of bioinformatics

Research Description
see Zhang Lab Research page

Halvey, PJ, Wang, X, Wang, J, Bhat, AA, Dhawan, P, Li, M, Zhang, B, Liebler, DC, Slebos, RJ. Proteogenomic analysis reveals unanticipated adaptations of colorectal tumor cells to deficiencies in DNA mismatch repair. Cancer Res, 74(1), 387-97, 2014

Wang, X, Zhang, B. Integrating genomic, transcriptomic, and interactome data to improve Peptide and protein identification in shotgun proteomics. J Proteome Res, 13(6), 2715-23, 2014

Zhang, B, Wang, J, Wang, X, Zhu, J, Liu, Q, Shi, Z, Chambers, MC, Zimmerman, LJ, Shaddox, KF, Kim, S, Davies, SR, Wang, S, Wang, P, Kinsinger, CR, Rivers, RC, Rodriguez, H, Townsend, RR, Ellis, MJ, Carr, SA, Tabb, DL, Coffey, RJ, Slebos, RJ, Liebler, DC, , , , , , , , . Proteogenomic characterization of human colon and rectal cancer. Nature, 2014

Liu, Q, Halvey, PJ, Shyr, Y, Slebos, RJ, Liebler, DC, Zhang, B. Integrative omics analysis reveals the importance and scope of translational repression in microRNA-mediated regulation. Mol Cell Proteomics, 2013

Liu, Q, Ullery, J, Zhu, J, Liebler, DC, Marnett, LJ, Zhang, B. RNA-seq data analysis at the gene and CDS levels provides a comprehensive view of transcriptome responses induced by 4-hydroxynonenal. Mol Biosyst, 9(12), 3036-46, 2013

Shi, Z, Wang, J, Zhang, B. NetGestalt: integrating multidimensional omics data over biological networks. Nat Methods, 10(7), 597-8, 2013

Wang, J, Duncan, D, Shi, Z, Zhang, B. WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): update 2013. Nucleic Acids Res, 2013

Wang, X, Zhang, B. customProDB: an R package to generate customized protein databases from RNA-Seq data for proteomics search. Bioinformatics, 29(24), 3235-7, 2013

Zhu, J, Wang, J, Shi, Z, Franklin, JL, Deane, NG, Coffey, RJ, Beauchamp, RD, Zhang, B. Deciphering genomic alterations in colorectal cancer through transcriptional subtype-based network analysis. PLoS One, 8(11), e79282, 2013

Halvey, PJ, Zhang, B, Coffey, RJ, Liebler, DC, Slebos, RJ. Proteomic consequences of a single gene mutation in a colorectal cancer model. J Proteome Res, 11(2), 1184-95, 2012 PMCID:3271737

Hardaway, JA, Hardie, SL, Whitaker, SM, Baas, SR, Zhang, B, Bermingham, DP, Lichtenstein, AJ, Blakely, RD. Forward genetic analysis to identify determinants of dopamine signaling in Caenorhabditis elegans using swimming-induced paralysis. G3 (Bethesda), 2(8), 961-75, 2012

Hoshino D, Jourquin J, Emmons SW, Miller T, Goldgof M, Costello K, Tyson DR, Brown B, Lu Y, Prasad NK, Zhang B, Mills GB, Yarbrough WG, Quaranta V, Seiki M, Weaver AM. Network analysis of the focal adhesion to invadopodia transition identifies a PI3K-PKC?? invasive signaling axis. Sci Signal, 5(241), ra66, 2012

Jourquin, J, Duncan, D, Shi, Z, Zhang, B. GLAD4U: deriving and prioritizing gene lists from PubMed literature. BMC Genomics, 13 Suppl 8, S20, 2012

Liu, Q, Guo, Y, Li, J, Long, J, Zhang, B, Shyr, Y. Steps to ensure accuracy in genotype and SNP calling from Illumina sequencing data. BMC Genomics, 13 Suppl 8, S8, 2012

Shi, M, Beauchamp, RD, Zhang, B. A network-based gene expression signature informs prognosis and treatment for colorectal cancer patients. PLoS One, 7(7), e41292, 2012

Sousa, JF, Ham, AJ, Whitwell, C, Nam, KT, Lee, HJ, Yang, HK, Kim, WH, Zhang, B, Li, M, LaFleur, B, Liebler, DC, Goldenring, JR. Proteomic profiling of paraffin-embedded samples identifies metaplasia-specific and early-stage gastric cancer biomarkers. Am J Pathol, 181(5), 1560-72, 2012

Wang, X, Slebos, RJ, Wang, D, Halvey, PJ, Tabb, DL, Liebler, DC, Zhang, B. Protein identification using customized protein sequence databases derived from RNA-Seq data. J Proteome Res, 11(2), 1009-17, 2012 PMCID:3285588

Angel, PM, Nusinow, D, Brown, CB, Violette, K, Barnett, JV, Zhang, B, Baldwin, HS, Caprioli, RM. Networked-based characterization of extracellular matrix proteins from adult mouse pulmonary and aortic valves. J Proteome Res, 10(2), 812-23, 2011

Li, J, Su, Z, Ma, ZQ, Slebos, RJ, Halvey, P, Tabb, DL, Liebler, DC, Pao, W, Zhang, B. A bioinformatics workflow for variant Peptide detection in shotgun proteomics. Mol Cell Proteomics, 10(5), M110.006536, 2011

Shi, M, Zhang, B. Semi-supervised learning improves gene expression-based prediction of cancer recurrence. Bioinformatics, 27(21), 3017-23, 2011 PMCID:3195453

Shi, Z, Zhang, B. Fast network centrality analysis using GPUs. BMC Bioinformatics, 12(1), 149, 2011

Zhang, B, Shi, Z, Duncan, DT, Prodduturi, N, Marnett, LJ, Liebler, DC. Relating protein adduction to gene expression changes: a systems approach. Mol Biosyst, 2011

Jing Li, Dexter T Duncan, Bing Zhang. CanProVar: a human cancer proteome variation database. Hum Mutat, 31(3), 219-228, 2010

Morabito, MV, Ulbricht, RJ, O''Neil, RT, Airey, DC, Lu, P, Zhang, B, Wang, L, Emeson, RB. High-throughput multiplexed transcript analysis yields enhanced resolution of 5HT2C receptor mRNA editing profiles. Mol Pharmacol, 2010

Smith, JJ, Deane, NG, Wu, F, Merchant, NB, Zhang, B, Jiang, A, Lu, P, Johnson, JC, Schmidt, C, Bailey, CE, Eschrich, S, Kis, C, Levy, S, Washington, MK, Heslin, MJ, Coffey, RJ, Yeatman, TJ, Shyr, Y, Beauchamp, RD. Experimentally derived metastasis gene expression profile predicts recurrence and death in patients with colon cancer. Gastroenterology, 138(3), 958-68, 2010

Wylie, CJ, Hendricks, TJ, Zhang, B, Wang, L, Lu, P, Leahy, P, Fox, S, Maeno, H, Deneris, ES. Distinct transcriptomes define rostral and caudal serotonin neurons. J Neurosci, 30(2), 670-84, 2010

Zhiao Shi, Catherine K Derow, Bing Zhang. Co-expression module analysis reveals biological processes, genomic gain, and regulatory mechanisms associated with breast cancer progression. BMC Syst Biol, 4, 74, 2010 PMCID:2902438

Heather L. Ball, Bing Zhang, Jacob Riches, Rikesh Gandhi, Jing Li, Johanna M. Rommens, Jeremy S. Myers. SBDS is a multi-functional protein implicated in cellular stress responses. Hum Mol Genet, 2009 PMCID:2742402

Jing Li, Lisa J Zimmerman, Byung-Hoon Park, David L Tabb, Daniel C Liebler, Bing Zhang. Network-assisted protein identification and data interpretation in shotgun proteomics. Mol Syst Biol, 5, 303, 2009 PMCID:2736651

Philip Gerlee, Docent T. Lundh, Bing Zhang, Alexander R.A. Anderson. Gene divergence and pathway duplication in the metabolic network of yeast and digital organisms. J R Soc Interface, 2009

Simona G. Codreanu, Bing Zhang, Scott M. Sobecki, Dean D. Billheimer, Daniel C. Liebler. Global analysis of protein damage by the lipid electrophile 4-hydroxy-2-nonenal. Mol Cell Proteomics, 8(4), 670-80, 2009 PMCID:2667350

Wang, L, Chen, X, Wolfinger, RD, Franklin, JL, Coffey, RJ, Zhang, B. A unified mixed effects model for gene set analysis of time course microarray experiments. Stat Appl Genet Mol Biol, 8(1), Article 47, 2009

Bing Zhang, Byung-Hoon Park, Tatiana Karpinets, Nagiza F. Samatova. From pull-down data to protein interaction networks and complexes with biological relevance. Bioinformatics, 24(7), 979-86, 2008

Chongle Pan, Yasuhiro Oda, Patricia K. Lankford, Bing Zhang, Nagiza F. Samatova, Dale A. Pelletier, Caroline S. Harwood, Robert L. Hettich. Characterization of anaerobic catabolism of p-coumarate in Rhodopseudomonas palustris by integrating transcriptomics and quantitative proteomics. Mol Cell Proteomics, 7(5), 938-48, 2008

Lily Wang, Bing Zhang, Russell D. Wolfinger, Xi Chen. An integrated approach for the analysis of biological pathways using mixed models. PLoS Genet, 4(7), e1000115, 2008 PMCID:2565842

Wilmes, P, Andersson, AF, Lefsrud, MG, Wexler, M, Shah, M, Zhang, B, Hettich, RL, Bond, PL, VerBerkmoes, NC, Banfield, JF. Community proteogenomics highlights microbial strain-variant protein expression within activated sludge performing enhanced biological phosphorus removal. ISME J, 2(8), 853-64, 2008

Xi Chen, Lily Wang, Jonathan D. Smith, Bing Zhang. Supervised principal component analysis for gene set enrichment of microarray data with continuous or survival outcomes. Bioinformatics, 24(21), 2474-81, 2008 PMCID:2732277

Zhang, B, Park, BH, Karpinets, T, Samatova, NF. From pull-down data to protein interaction networks and complexes with biological relevance. Bioinformatics, 24(7), 979-86, 2008

Bing Zhang, Matthew C. Chambers, David L. Tabb. Proteomic parsimony through bipartite graph analysis improves accuracy and transparency. J Proteome Res, 6(9), 3549-57, 2007

Stefan A. Kirov, Bing Zhang, Jay R. Snoddy. Association analysis for large-scale gene set data. Methods Mol Biol, 408, 19-33, 2007

Bing Zhang, Nathan C. VerBerkmoes, Michael A. Langston, Edward Uberbacher, Robert L. Hettich, Nagiza F. Samatova. Detecting Differential and Correlated Protein Expression in Label-Free Shotgun Proteomics. J Proteome Res, 5(11), 2909-2918, 2006

Bing Zhang, Stefan A. Kirov, Jay R. Snoddy. WebGestalt: an integrated system for exploring gene sets in various biological contexts. Nucleic Acids Res, 33(Web Server issue), W741-8, 2005 PMCID:1160236

Nicole E. Baldwin, Elissa J. Chesler, Stefan A. Kirov, Michael A. Langston, Jay R. Snoddy, Robert W. Williams, Bing Zhang. Computational, integrative, and comparative methods for the elucidation of genetic coexpression networks. J Biomed Biotechnol, 2005(2), 172-80, 2005 PMCID:1184052

Stefan A. Kirov, Xinxia Peng, Eric Baker, Denise Schmoyer, Bing Zhang, Jay R. Snoddy. GeneKeyDB: a lightweight, gene-centric, relational database to support data mining environments. BMC Bioinformatics, 6, 72, 2005 PMCID:1274265

Bing Zhang, Denise Schmoyer, Stefan Kirov, Jay Snoddy. GOTree Machine (GOTM): a web-based platform for interpreting sets of interesting genes using Gene Ontology hierarchies. BMC Bioinformatics, 5, 16, 2004 PMCID:373441

Sumithra Urs, Colton Smith, Brett Campbell, Arnold M. Saxton, James Taylor, Bing Zhang, Jay Snoddy, Brynn Voy, Naima Moustaid-Moussa. Gene expression profiling in human preadipocytes and adipocytes by microarray analysis. J Nutr, 134(4), 762-70, 2004

Bing Zhang, Katrina M. Ramonell, Shauna Somerville, Gary Stacey. Characterization of early, chitin-induced gene expression in Arabidopsis. Mol Plant Microbe Interact, 15(9), 963-70, 2002

Katrina M. Ramonell, Bing Zhang, Yu Chen, Dong Xu, Gary Stacey, Shauna Somerville. Microarray analysis of chitin elicitation in Arabidopsis. Mol Plant Pathol, 3(5), 301-311, 2002

Postdoctoral Position Available

Postdoctoral Position Details
Postdoctoral Position in Proteo-genomic data integration

A postdoctoral research scientist position is available to study proteo-genomic data integration in Dr. Bing Zhang''''s group at the Department of Biomedical Informatics, Vanderbilt University. We are involved in several large projects that collect multidimensional omics data at DNA, mRNA and protein levels for the same set of biological samples. Although big data presents big opportunities, integrative analysis of these different types of data is complex and challenging. The postdoctoral research scientist is expected to develop innovative proteo-genomic data integration approaches that help reveal novel biological insights from multidimensional omics data. Some examples can be found in our recent publications: Liu et al. MCP, 2013; Wang et al. JPR, 2012; Li et al. MCP, 2011; and Zhang et al. Mol Biosyst, 2011. We are particularly interested in understanding how genomic alterations affect protein output and activity, and how this information can be used to improve disease management.

The position offers an excellent opportunity to conduct research in a supportive and stimulating environment, and to collaborate with bioinformaticians, biostatisticians, computer scientists, and biologists.

Required Skills:
1. At least 3 years experience in one or more of the following languages: Perl, Python, C, C++
2. Strong programming skills in R
3. Hands-on experience with next generation sequencing and/or shotgun proteomics data analysis
4. Good spoken and written communication skills, with the later supported by peer-reviewed publications

Desired Skills:
1. Knowledge of molecular biology
2. Experience with machine learning algorithms
3. Experience with web application and database development

Candidates must have a Ph. D. in bioinformatics, computer science, biostatistics, biology, or a related field.

How to Apply:
Please send a cover letter and CV to Bing Zhang at

Updated Date