Learning generative models of molecular dynamics

We introduce three algorithms for learning generative models of molecular structures from molecular dynamics simulations. The first algorithm learns a Bayesian-optimal undirected probabilistic model over user-specified covariates (e.g., fluctuations, distances, angles, etc). L(1 )reg-ularization is...

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Detalles Bibliográficos
Autores principales: Razavian, Narges Sharif, Kamisetty, Hetunandan, Langmead, Christopher J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3394414/
https://www.ncbi.nlm.nih.gov/pubmed/22369071
http://dx.doi.org/10.1186/1471-2164-13-S1-S5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3394414/
https://www.ncbi.nlm.nih.gov/pubmed/22369071
http://dx.doi.org/10.1186/1471-2164-13-S1-S5

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