Bing Zhang, Ph.D.
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Bing Zhang, Ph.D.
Professor
Positions
- Professor
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Lester and Sue Smith Breast Center
Baylor College of Medicine
Houston, TX US
- Professor
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Department of Molecular and Human Genetics
Baylor College of Medicine
- Member
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Dan L Duncan Comprehensive Cancer Center
Baylor College of Medicine
Houston, Texas United States
- McNair Scholar
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Baylor College of Medicine
Houston, Texas United States
- Faculty Member
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Graduate Program in Quantitative and Computational Biosciences
Baylor College of Medicine
- Faculty Member
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Graduate Program in Cancer and Cell Biology
Baylor College of Medicine
Addresses
- BCM-Jewish Building (Office)
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Room: 648D
Houston, TX 77030
United States
Phone: (713) 798-1443
bing.zhang@bcm.edu
Education
- BS from Nanjing University
- Nanjing, China
- PhD from Chinese Academy of Sciences
- Shanghai, China
- Postdoctoral Training at Oak Ridge National Laboratory
- Oak Ridge, Tennessee United States
Honors & Awards
- CPRIT Scholar in Cancer Research
- Cancer Prevention Research Institute of Texas (09/2016)
- McNair Scholar
- McNair Medical Institute (08/2016)
- Gilbert S. Omenn Computational Proteomics Award
- US Human Proteome Organization (03/2023)
- Michael E. DeBakey Excellence in Research Award
- Baylor College of Medicine (05/2024)
Professional Interests
- Bioinformatics
- Systems biology
- Precision oncology
Professional Statement
My research interests encompass the broad areas of bioinformatics, computational proteomics, proteogenomics and cancer systems biology. During the past decade, through support from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC), I have established an internationally recognized research program in computational cancer proteogenomics, focusing on integrating genomic and proteomic data to better understand cancer biology and to improve cancer diagnosis and treatment. My group led the first integrative proteogenomic characterization of human cancer in a colorectal cancer cohort, which was published in Nature in 2014. The proteogenomics approach has now been applied to more than 10 cancer types within and outside CPTAC. My group participated in fourteen proteogenomics studies published in Nature, Cell and Cancer Cell. Together, these studies have demonstrated that integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and that proteogenomics holds great potential to enable new advances in cancer biology, diagnosis, prognosis and targeted and immunotherapies.To facilitate omics and multi-omics data analysis, my group has developed multiple widely used bioinformatics tools. CustomProDB is one of the first computational proteogenomics tools, and its expansion into NeoFlow enables proteogenomics-based neoantigen prioritization. The pathway and network analysis tool WebGestalt has been serving the biology research community for 17 years. In 2021 alone, WebGestalt was used >160,000 times by >56,000 users and was cited in >900 papers. The LinkedOmics web application makes multi-omics data from CPTAC and TCGA directly available and useful to the cancer research community. Published in 2018, the tool has already been used >150,000 times by >57,000 users, with >1000 citations.
Cancer proteogenomics is becoming a “data-rich” field. My team will continue developing bioinformatics methods and tools to expedite the extraction of novel biological and clinical insights from the continually growing volume of data. We are also working actively with clinical collaborators to translate data-driven computational discoveries into treatment advances for patients.
Websites
Selected Publications
- Wen B, Wang C, Li K, Han P, Holt MV, Savage SR, Lei JT, Dou Y, Shi Z, Li Y, Zhang B. "DeepMVP: deep learning models trained on high-quality data accurately predict PTM sites and variant-induced alterations.." Nat Methods.. 2025; Pubmed PMID: 40859022
- Shi Z, Lei JT, Elizarraras JM, Zhang B "Mapping the functional network of human cancer through machine learning and pan-cancer proteogenomics." Nat Cancer.. 2025;6(1):205-222. Pubmed PMID: 39663389
- Savage SR, Yi X, Lei JT, Wen B, Zhao H, Liao Y, Jaehnig EJ, Somes LK, Shafer PW, Lee TD, Fu Z, Dou Y, Shi Z, Gao D, Hoyos V, Gao Q, Zhang B. "Pan-cancer proteogenomics expands the landscape of therapeutic targets.." Cell.. 2024;187(16) Pubmed PMID: 38917788
- Vasaikar S, Huang C, Wang X, Petyuk VA, Savage SR, Wen B, Dou Y, Zhang Y, Shi Z, Arshad OA, Gritsenko MA, Zimmerman LJ, McDermott JE, …... Ellis M, Thiagarajan M, Kinsinger CR, Rodriguez H, Smith RD, Rodland KD, Liebler DC, Liu T, Zhang B, CPTAC "Proteogenomic analysis of human colon cancer reveals new therapeutic opportunities." Cell. 2019;177:1035-1049. Pubmed PMID: 31031003
- 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, CPTAC "Proteogenomic characterization of human colon and rectal cancer." Nature. 2014;513:382-387. Pubmed PMID: 25043054
Funding
- IPGDAC, an integrative proteogenomic data analysis center for CPTAC NIH/NCI
- Proteogenomics-driven therapeutic discovery in hepatocellular carcinoma NIH/NCI
- Signaling network modeling to identify new treatments for triple-negative breast cancer CPRIT
- Advancing Protein Isoform Analysis through an Integrated Computational Framework NIH/NCI
- Charting TCR- Tumor Antigen Interactions to Foster Novel Immunotherapeutic Approaches for Triple-Negative Breast Cancer CPRIT
- Targeting Cryptic Splicing-Derived Neoantigens in hnRNPM-Dysregulated Triple-Negative Breast Cancer DOD
- mRNA-based immunotherapy for targeting triple-negative breast cancer V Foundation
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