Optimized parameter selection reveals trends in Markov state models for protein folding.
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Bridging Microscopic and Macroscopic Mechanisms of p53-MDM2 Binding with Kinetic Network Models.Note: MSM lag time cannot be used for variational model selection.Folding a viral peptide in different membrane environments: pathway and sampling analyses.Constructing Markov State Models to elucidate the functional conformational changes of complex biomolecules
P2860
Optimized parameter selection reveals trends in Markov state models for protein folding.
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2016 nî lūn-bûn
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2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
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name
Optimized parameter selection reveals trends in Markov state models for protein folding.
@en
Optimized parameter selection reveals trends in Markov state models for protein folding.
@nl
type
label
Optimized parameter selection reveals trends in Markov state models for protein folding.
@en
Optimized parameter selection reveals trends in Markov state models for protein folding.
@nl
prefLabel
Optimized parameter selection reveals trends in Markov state models for protein folding.
@en
Optimized parameter selection reveals trends in Markov state models for protein folding.
@nl
P2860
P356
P1476
Optimized parameter selection reveals trends in Markov state models for protein folding
@en
P2093
Robert T McGibbon
Vijay S Pande
P2860
P304
P356
10.1063/1.4967809
P407
P577
2016-11-01T00:00:00Z