Protein folding and phylogenetic tree reconstruction using stochastic approximation Monte Carlo

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Title: Protein folding and phylogenetic tree reconstruction using stochastic approximation Monte Carlo
Author: Cheon, Sooyoung
Abstract: Recently , the stochastic approximation Monte Carlo algorithm has been proposed by Liang et al . (2005 ) as a general -purpose stochastic optimization and simulation algorithm . An annealing version of this algorithm was developed for real small protein folding problems . The numerical results indicate that it outperforms simulated annealing and conventional Monte Carlo algorithms as a stochastic optimization algorithm . We also propose one method for the use of secondary structures in protein folding . The predicted protein structures are rather close to the true structures . Phylogenetic trees have been used in biology for a long time to graphically represent evolutionary relationships among species and genes . An understanding of evolutionary relationships is critical to appropriate interpretation of bioinformatics results . The use of the sequential structure of phylogenetic trees in conjunction with stochastic approximation Monte Carlo was developed for phylogenetic tree reconstruction . The numerical results indicate that it has a capability of escaping from local traps and achieving a much faster convergence to the global likelihood maxima than other phylogenetic tree reconstruction methods , such as BAMBE and MrBayes .
URI: http : / /hdl .handle .net /1969 .1 /5785
Date: 2007-09-17

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Protein folding and phylogenetic tree reconstruction using stochastic approximation Monte Carlo. Available electronically from http : / /hdl .handle .net /1969 .1 /5785 .

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