Computational Biology and Bioinformatics  
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Cancer Genomics and Precision Medicine

Cancer is one of the leading causes of death and is the most costly disease. Using computational and integrative approaches, we aim to understand better the heterogeneity of cancer and apply the understanding to precision medicine.

Selected publications in cancer health disparities:

Selected publications in precision medicine:

  • Kaixian Yu, Qingxiang Amy Sang, Winston Tan, Mayassa B Dargham, Ty Lively, Cedric Shefield, Jun S Liu, Jinfeng Zhang, Personalized chemotherapy regimen selection for breast cancer. Proceedings of AACR 2016. Abstract # 2034.

Biological text mining and knowledge discovery

Traditionally, biomedical knowledge is stored in scientific publications. Reading published papers, reviews and books is the way to grasp what has been discovered and known in a particular scientific field. As scientific publications are being accumulated at an ever increasing speed, automatic extraction and effective organization of such information become critical for the integrative analysis of existing knowledge and experimental data.

Selected publication and database/webserver:

Lindsey Bell, Rajesh Chowdhary, Jun S Liu, Xufeng Niu, Jinfeng Zhang. Integrated bio-entity network: a system for biological knowledge discovery. PLoS ONE, 2011, 6(6): e21474, doi:10.1371/journal.pone.0021474.

R Chowdhary, J Zhang, JS Liu. Bayesian Inference of Protein-protein Interactions from Biological Literature , Bioinformatics, 25(12), 1536-1542 (2009).

An integrated molecular interaction database

Understanding the sequence-structure-function relationship of proteins

Proteins, the machines of life, are involved in most biological processes. Protein functions are determined by their structures, which is in turn determined by their sequences. We aim to achieve a better understanding of the sequence-structure-function relationship of proteins through computational approaches. In the past, we have worked on various problems from protein packing, energy functions for simplified models, side chain packing and side chain entropy, protein interactions, protein folding, loop modeling, and structure prediction.

Selected publications:

J Laborde, D Robinson, A Srivastava, E Klassen and J Zhang, RNA global alignment in the joint sequence-structure space using Elastic Shape Analysis, Nucl. Acids Res. (2013) 41 (11): e114. doi: 10.1093/nar/gkt187

W Liu, A Srivastava, J Zhang. A mathematical framework for protein structure comparison. PLoS Computational Biology 7(2), (2011): e1001075. doi:10.1371/journal.pcbi.1001075.

J Zhang, SC Kou, JS Liu. Biopolymer structure simulation and optimization via fragment regrowth Monte Carlo. Journal of Chemical Physics, 126, 225101, (2007).

J Zhang, M Lin, R Chen, J Liang, JS Liu. Monte Carlo sampling of near-native structures of proteins and applications, Proteins, 66, 61-68, (2007)

J Zhang, JS Liu. On side-chain conformational entropy of proteins. PLoS Computational Biology, 2(12): e168. doi:10.1371/journal.pcbi.0020168, (2006)



Contact Information

Jinfeng Zhang, Ph.D.
Department of Statistics
Florida State University

106E OSB
117 N. Woodward Ave.
Tallahassee, FL
Tel: (850) 644-3218
Fax: (850) 644-5271