Stochastic Optimization Based Study of Dimerization Kinetics
Abstract
We investigate the potential of numerical algorithms to decipher the kinetic parameters involved in multi-step chemical reactions. To this end we study a dimerization kinetics of protein as a model system. We follow the dimerization kinetics using a stochastic simulation algorithm and combine it with three different optimization techniques (Genetic Algorithm, Simulated Annealing and Parallel Tempering) to obtain the rate constants involved in each reaction step. We find good convergence of the numerical scheme to the rate constants of the process. We also perform a sensitivity test on the reaction kinetic parameters to see the relative effects of the parameters for the associated profile of the monomer/dimer distribution.
Cite
@article{arxiv.1310.6503,
title = {Stochastic Optimization Based Study of Dimerization Kinetics},
author = {Srijeeta Talukder and Shrabani Sen and Ralf Metzler and Suman K Banik and Pinaki Chaudhury},
journal= {arXiv preprint arXiv:1310.6503},
year = {2014}
}
Comments
19 pages, 6 figures