dc.creatorGonzález-Alemán, Roy
dc.creatorHernández-Castillo, David
dc.creatorRodríguez-Serradet, Alejandro
dc.creatorCaballero, Julio
dc.creatorHernández-Rodríguez, Erix W.
dc.creatorMontero-Cabrera, Luis
dc.date2023-05-08T19:03:18Z
dc.date2023-05-08T19:03:18Z
dc.date2020
dc.date.accessioned2024-05-02T20:31:10Z
dc.date.available2024-05-02T20:31:10Z
dc.identifierhttp://repositorio.ucm.cl/handle/ucm/4749
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9274987
dc.descriptionThe growing computational capacity allows the investigation of large biomolecular systems by increasingly extensive molecular dynamics simulations. The resulting huge trajectories demand efficient partition methods to discern relevant structural dissimilarity. Clustering algorithms are available to address this task, but their implementations still need to be improved to gain in computational speed and to reduce the consumption of random access memory. We propose the BitClust code which, based on a combination of Python and C programming languages, performs fast structural clustering of long molecular trajectories. BitClust takes advantage of bitwise operations applied to a bit-encoded pairwise similarity matrix. Our approach allowed us to process a half-million frame trajectory in 6 h using less than 35 GB, a task that is not affordable with any of the similar alternatives.
dc.languageen
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Chile
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
dc.sourceJournal of Chemical Information and Modeling, 60(2), 444-448
dc.titleBitClust: fast geometrical clustering of long molecular dynamics simulations
dc.typeArticle


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