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Dr. Zhen Zhang

(410) 502-7871 (p)

Associate Professor, Pathology

Research Summary

My research interests are in the development and application of bioinformatics tools for clinical diagnosis. What used to be considered as a single diagnosis may actually consist of a number of different phenotypes with distinguished disease pathways and varying genomic and proteomics expression patterns. I am interested in deriving new mathematical and computational algorithms to identify such patterns for biomarker discovery and use them to establish predictive models for the diagnosis and management of diseases. Currently, our effort is focused on tumor marker discovery using high throughput proteomics approaches. 

Journal Citations

Zhang Z., Barnhill S.D., Zhang H., Xu F., Yu Y., Jacobs I., Woolas R.P., Berchuck A., Madyastha K.R., Bast R.C. Jr. Combination of multiple serum markers using an artificial neural network to improve specificity in discriminating malignant from benign pelvic masses. Gynecol Oncol. 1999; 73(1):56-61.
Li J, Zhang Z., Rosenzweig J., Wang Y., Chan D.W. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin. Chem., 2002 Aug;48(8):1296-1304.

Zhang Z. Combining Multiple Biomarkers in Clinical Diagnostics - A review of Methods and Issues. In: Diamandis E.P., Fritsche H.A., Lilja H.,Chan D.W., Schwartz M.K., eds. Tumor Markers: Physiology, Pathobiology, Technology and Clinical Applications. AACC Press, Washington, DC, 2002.

Buckhaults P., Zhang Z., Chen Y.C., Wang T.L., St Croix B., Saha S., Bardelli A., Morin P.J., Polyak K., Hruban R.H., Velculescu V.E., Shih IeM. Identifying tumor origin using a gene expression-based classification map. Cancer Res. 2003; 63(14):4144-9.

Zhang Z., Bast R.C. Jr, Yu Y., Li J., Sokoll L.J., Rai A.J., Rosenzweig J.M., Cameron B., Wang Y.Y., Meng X.Y., Berchuck A., Van Haaften-Day C., Hacker N.F., de Bruijn H.W., van der Zee A.G., Jacobs I.J., Fung E.T., Chan D.W. Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer. Cancer Res. 2004; 64(16):5882-90.


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