Outer memberane protein (Omp) channel as bionanopore has emerged as an important class of molecular sensor that has the promise of detecting a wide variety of molecules through measurment of gating signals. Chromosome folding in three-dimensional space provides important control mechanism for selective activation and repression of gene expression. In both cases, characterizing conformational ensembles of chain polymers in the form of protein loops and chromatin loops are of central important. We discuss recent progresses in deep sampling for studying channel loop ensembles and chromatin ensembles, and present results on OmpG gating mechanism and on discovery of specific interactions of chromatin folding. These results can be useful for developing mathematical theories and models to gain additional conceptual understanding on these important biological problems.

Bio:

Jie Liang is a Richard and Loan Hill professor in the Richard and Loan Hill Department of Bioengineering at the University of Illinois at Chicago. He joined UIC in 1999 as an assistant professor, and was promoted to associated professor in 2003, and to full professor in 2007. He received his B.S. degree in Biophysics from Fudan University in 1986, MCS and Ph.D. in Biophysics from the University of Illinois at Urbana-Champaign in 1994. He was an NSF CISE postdoctoral research associate (1994-1996) at the Beckman Institute and National Center for Supercomputing and its Applications (NCSA) in Urbana, IL. He spent eight months as a visiting fellow at the NSF Institute of Mathematics and Applications at Minneapolis. From 1997 to 1999, he was an Investigator at SmithKline Beecham Pharmaceuticals in Philadelphia. He was a recipient of the NSF CAREER award in 2003. He was elected as a fellow of the American Institue of Medicine and Biological Engineering in 2007. He is a University Scholar.

Dr. Liang's research interests include bioinformatics, systems biology, mechanobiology, computational biophysics, especially the areas of structural bioinformatics, computational proteomics, molecular stochastic networks, and cellular pattern formation. Current projects in his lab include protein function prediction, evolution analysis, membrane protein/nanodevice assembly, stochastic networks, polarity, and tissue pattern formation. His recent work can be found at (gila.bioe.uic.edu/liang/liang_pub.html).