Computational Biology and Bioinformatics  
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Research

 

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)


Systems and integrative approaches for cancer research

Cancer is one of the leading causes of death. Using computational and integrative approaches, we aim to achieve system-level understanding of the mechanism of cancer to identify drug target and develop treatment more effectively. Currently, we are working on health disparity and personalized therapy for cancer.

Selected publications:

P A Stewart, J Luks, M D Roycik, Q A Sang, and J Zhang (2013) Differentially Expressed Transcripts and Dysregulated Signaling Pathways and Networks in African American Breast Cancer. PLoS One, 8(12): e82460.


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).

Protein-protein interaction extraction server: BioTextMiner.com

An integrated molecular interaction database: IntegrativeBiology.org



 

 

Contact Information

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

106E OSB
117 N. Woodward Ave.
Tallahassee, FL
32306-4330
Tel: (850) 644-3218
Fax: (850) 644-5271
Email: jinfeng@stat.fsu.edu