Tackling the protein folding problem by a generalized-ensemble approach with Tsallis statistics

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/123456789/2549

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DC Field	Value	Language
dc.creator	Hansmann Ulrich H.E.	-
dc.creator	Okamoto Yuko	-
dc.date	1999	-
dc.date.accessioned	2013-05-29T22:53:49Z	-
dc.date.available	2013-05-29T22:53:49Z	-
dc.date.issued	2013-05-30	-
dc.identifier	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-97331999000100017	-
dc.identifier	http://www.doaj.org/doaj?func=openurl&genre=article&issn=01039733&date=1999&volume=29&issue=1&spage=187	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/jspui/handle/123456789/2549	-
dc.description	We review uses of Tsallis statistical mechanics in the protein folding problem. Monte Carlo simulated annealing algorithm and generalized-ensemble algorithm with both Monte Carlo and stochastic dynamics algorithms are discussed. Simulations by these algorithms are performed for a penta peptide, Met-enkephalin. In particular, for generalized-ensemble algorithms, it is shown that from only one simulation run one can find the global-minimum-energy conformation and obtain probability distributions in canonical ensemble for a wide temperature range, which allows the calculation of any thermodynamic quantity as a function of temperature.	-
dc.publisher	Sociedade Brasileira de Física	-
dc.source	Brazilian Journal of Physics	-
dc.title	Tackling the protein folding problem by a generalized-ensemble approach with Tsallis statistics	-
Appears in Collections:	Physics and Astronomy

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