Local and Stochastic WHAM and Applications in Computational Biophysics

• Activity Number: 511
• Type: Invited
• Date/Time: Wednesday, August 12, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistical Computing
• Author(s): Zhiqiang Tan* and Bin Zhang and Ronald Levy
• Companies: ASA and Temple University and Temple University
• Keywords: normalizing constant ; free energy ; weighted histogram analysis method ; stochastic approximation

Abstract

The weighted histogram analysis method (WHAM) has been developed in several different contexts independently, and widely used in chemistry, physics and biophysics, and in statistics, using observations simulated from multiple distributions, corresponding for physical systems to multiple thermodynamic states. The method provides not only estimates of normalizing constants or equivalently free energies, but also estimates of the individual distributions based on the observations from all states. However, this method, while statistically efficient, is computationally costly or even impractical when a large number (e.g., hundreds or thousands) of distributions are involved. We develop local and stochastic approximations to WHAM estimates, with much reduced computational cost. Applications to analysis of complex chemical and biophysical systems will be discussed.