Yaoqi Zhou
Academic Editor

Yaoqi Zhou


Summary

Professor Zhou was graduated with BS in Chemical Physics from University of Science and Technology of China in 1984 and a PhD in Chemical Physics from State University of New York at Stony Brook in 1990. He switched his research field to computational biology when he was a postdoctoral research fellow at Harvard University with Professor Martin Karplus from 1995 t0 2000. He was an Assistant Professor and later Associate Professor at Department of Physiology and Biophysics at State University of New York at Buffalo from 2000 to 2006 and became a full Professor when he joined Indiana University School of Informatics at Indianapolis in 2006. He was a director of Bioinformatics program at the School of Informatics since 2007. Starting June 2013, He joined School of Information and Communication Technology and Institute for Glycomics at Griffith University as a Professor of Computational Biology. Dr. Zhou has published more than 170 peer reviewed articles and is known for his widely used bioinformatics tools such as SPARKS for protein structure prediction and DFIRE for protein binding and folding scoring functions.

Bioinformatics Biophysics Computational Biology Computer Aided Design

Institution affiliations

Work details

Research Leader/Professor

Griffith University
June 2013
Institute for Glycomcis
Our group are working at the cutting-edge of the modern biotechnology that integrates computational and experimental approaches for rational design of therapeutic small and biologic drugs. Biologic drugs such as proteins are medicinal products extracted from living systems. Unlike small molecular drugs, they are more specific to the intended target (i.e. less toxicity) and have enjoyed much higher success rate in every phase of clinical trials. However, unlike small molecules, biologic drugs are expensive to manufacture due to low yields. The objectives of our research in this area are to increase protein drug production by codon optimisation and to design peptides or proteins with specific therapeutic effects. In addition to working in the area of biologic drug discovery, our group is actively developing the next-generation computational technique for small-molecule inhibitor design. Another area of our research is to build an integrated, clinically useful tool for predicting disease susceptibility from individual genetic variations, the key element of the upcoming era of personalized medicine. These studies are built on many bioinformatics tools that have been established or to be established soon.