Computational Biology and Bioinformatics  
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AI-powered 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.
We have developed a deep learning-powered search engine for biomedical literature, which can be accessed at

Selected publication and database/webserver:

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:

Omics data analysis methods

We have also developed methods for omics data analysis including gene expression data and epigenomics data.

Selected publications in methods for omics data analysis:

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:



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