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Assessing the performance of stochastic optimization methods in structural modelling

Supervisor

Suitable for

Computer Science and Philosophy, Part B
Computer Science and Philosophy, Part C
Computer Science, Part B
Computer Science, Part C

Abstract

The efficiency of Monte Carlo (MC) based stochastic optimization methods (e.g. Kirkpatrick, et al. Science, 220, 671–680 (1983)) are compared to find low energy conformational states of a given system. We are particularly interested in MC protocols where the temperature varies as a series of impulses followed by relaxation and only the temperature of a given part (e.g. site of interest) of the system is changed.

Prerequisites:  Recommended for students who has done the Probability and Computing and Geometric Modelling courses and have interest in randomized search methods and their applications in structural biology.