![chiangts [at] comp.nus.edu.sg](email.jpg)
I'm a Computer Science Ph.D. student at the National University of Singapore.
My advisors are David Hsu and Jean-Claude Latombe from Stanford University.
The molecular motion of proteins is the aggregate result of complex atomic interactions over several magnitudes of timescales.
However, the huge amounts of molecular dynamics trajectories required for a realistic simulation is difficult to analyze and comprehend.
My work circumvents this difficulty by modeling molecular motion as a Markov dynamic process.
The proposed solution compactly represents the motion as probabilistic transitions across a hierarchy of states, over a range of timescales.
The resulting model accurately predicts the motion dynamics, and more crucially, allows scientists to gain a better understanding of the natural phenomenon.
Markov Dynamic Models for Long-Timescale Protein Motion
Tsung-Han Chiang, David Hsu, and Jean-Claude Latombe
Markov Dynamic Models for Long-Timescale Protein Motion
Bioinformatics, Special issue on Int. Conf. on Intelligent Systems for Molecular Biology (ISMB), 26:i269-i277, 2010
Tsung-Han Chiang, Mehmet Serkan Apaydin, Douglas L. Brutlag, David Hsu, and Jean-Claude Latombe
Using Stochastic Roadmap Simulation to Predict Experimental Quantities in Protein Folding Kinetics: Folding Rates and Phi-Values
Journal of Computational Biology, 14(5):578-593, 2007
Tsung-Han Chiang, Mehmet Serkan Apaydin, Douglas L. Brutlag, David Hsu, and Jean-Claude Latombe
Predicting Experimental Quantities in Protein Folding Kinetics Using Stochastic Roadmap Simulation
In Proc. ACM Int. Conf. on Computational Biology (RECOMB), pages 410-424, 2006