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Campo DC | Valor | Lengua/Idioma |
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dc.contributor.author | Jaillet, Léonard | - |
dc.contributor.author | Corcho, Francesc J. | - |
dc.contributor.author | Pérez, Juan Jesús | - |
dc.contributor.author | Cortés, Juan | - |
dc.date.accessioned | 2014-05-19T11:26:03Z | - |
dc.date.available | 2014-05-19T11:26:03Z | - |
dc.date.issued | 2011 | - |
dc.identifier | doi: 10.1002/jcc.21931 | - |
dc.identifier | issn: 0192-8651 | - |
dc.identifier | e-issn: 1096-987X | - |
dc.identifier.citation | Journal of Computational Chemistry 32(16): 3464-3474 (2011) | - |
dc.identifier.uri | http://hdl.handle.net/10261/96864 | - |
dc.description.abstract | In this work, a new method for exploring conformational energy landscapes is described. The method, called transition-rapidly exploring random tree (T-RRT), combines ideas from statistical physics and robot path planning algorithms. A search tree is constructed on the conformational space starting from a given state. The tree expansion is driven by a double strategy: on the one hand, it is naturally biased toward yet unexplored regions of the space; on the other, a Monte Carlo-like transition test guides the expansion toward energetically favorable regions. The balance between these two strategies is automatically achieved due to a self-tuning mechanism. The method is able to efficiently find both energy minima and transition paths between them. As a proof of concept, the method is applied to two academic benchmarks and the alanine dipeptide. Copyright © 2011 Wiley Periodicals, Inc. | - |
dc.description.sponsorship | Funded by: Spanish Ministry of Science and Innovation. Grant Number: DPI2010-18449 and CSIC (JAE-Doc fellowship to L. J.). | - |
dc.publisher | John Wiley & Sons | - |
dc.relation.isversionof | Postprint | - |
dc.rights | openAccess | - |
dc.subject | Robot path planning algorithms | - |
dc.subject | Monte Carlo methods | - |
dc.subject | Conformational transition paths | - |
dc.subject | Peptides | - |
dc.subject | Energy landscape exploration | - |
dc.title | Randomized tree construction algorithm to explore energy landscapes | - |
dc.type | artículo | - |
dc.identifier.doi | 10.1002/jcc.21931 | - |
dc.relation.publisherversion | http://dx.doi.org/10.1002/jcc.21931 | - |
dc.date.updated | 2014-05-19T11:26:04Z | - |
dc.description.version | Peer Reviewed | - |
dc.language.rfc3066 | eng | - |
dc.type.coar | http://purl.org/coar/resource_type/c_6501 | es_ES |
item.openairetype | artículo | - |
item.grantfulltext | open | - |
item.cerifentitytype | Publications | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | With Fulltext | - |
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Randomized tree.pdf | 897,51 kB | Adobe PDF | Visualizar/Abrir |
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