Email

bing.zhang@bcm.edu

Positions

Professor

Lester and Sue Smith Breast Center
Baylor College of Medicine
Houston, TX US

Professor

Department of Molecular and Human Genetics
Baylor College of Medicine

Member

Dan L Duncan Comprehensive Cancer Center
Baylor College of Medicine
Houston, Texas United States

McNair Scholar

Baylor College of Medicine
Houston, Texas United States

Faculty Member

Graduate Program in Quantitative and Computational Biosciences
Baylor College of Medicine

Faculty Member

Graduate Program in Cancer and Cell Biology
Baylor College of Medicine

Addresses

BCM-Jewish Building (Office)

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 - 08/2021)

McNair Scholar

McNair Medical Institute (08/2016 - 07/2024)

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

• 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
• Vasaikar SV, Straub P, Wang J, Zhang B "LinkedOmics: analyzing multi-omics data within and across 32 cancer types." Nucleic Acids Res. 2018;46:D956-D963. Pubmed PMID: 29136207
• Wen B, Li K, Zhang Y, Zhang B "Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis." Nat Commun. 2020;11(1):1759. Pubmed PMID: 32273506

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

Illuminating understudied druggable proteins using pan-cancer proteogenomics data

NIH/NCI