254 related articles for article (PubMed ID: 26574199)
1. Automatic state partitioning for multibody systems (APM): an efficient algorithm for constructing Markov state models to elucidate conformational dynamics of multibody systems.
Sheong FK; Silva DA; Meng L; Zhao Y; Huang X
J Chem Theory Comput; 2015 Jan; 11(1):17-27. PubMed ID: 26574199
[TBL] [Abstract][Full Text] [Related]
2. Application of Markov State Models to simulate long timescale dynamics of biological macromolecules.
Da LT; Sheong FK; Silva DA; Huang X
Adv Exp Med Biol; 2014; 805():29-66. PubMed ID: 24446356
[TBL] [Abstract][Full Text] [Related]
3. Markov state models provide insights into dynamic modulation of protein function.
Shukla D; Hernández CX; Weber JK; Pande VS
Acc Chem Res; 2015 Feb; 48(2):414-22. PubMed ID: 25625937
[TBL] [Abstract][Full Text] [Related]
4. Constructing Kinetic Network Models to Elucidate Mechanisms of Functional Conformational Changes of Enzymes and Their Recognition with Ligands.
Zhang L; Jiang H; Sheong FK; Pardo-Avila F; Cheung PP; Huang X
Methods Enzymol; 2016; 578():343-71. PubMed ID: 27497174
[TBL] [Abstract][Full Text] [Related]
5. Hierarchical Nyström methods for constructing Markov state models for conformational dynamics.
Yao Y; Cui RZ; Bowman GR; Silva DA; Sun J; Huang X
J Chem Phys; 2013 May; 138(17):174106. PubMed ID: 23656113
[TBL] [Abstract][Full Text] [Related]
6. Elucidation of the conformational dynamics of multi-body systems by construction of Markov state models.
Zhu L; Sheong FK; Zeng X; Huang X
Phys Chem Chem Phys; 2016 Nov; 18(44):30228-30235. PubMed ID: 27314275
[TBL] [Abstract][Full Text] [Related]
7. Automatic discovery of metastable states for the construction of Markov models of macromolecular conformational dynamics.
Chodera JD; Singhal N; Pande VS; Dill KA; Swope WC
J Chem Phys; 2007 Apr; 126(15):155101. PubMed ID: 17461665
[TBL] [Abstract][Full Text] [Related]
8. Constructing multi-resolution Markov State Models (MSMs) to elucidate RNA hairpin folding mechanisms.
Huang X; Yao Y; Bowman GR; Sun J; Guibas LJ; Carlsson G; Pande VS
Pac Symp Biocomput; 2010; ():228-39. PubMed ID: 19908375
[TBL] [Abstract][Full Text] [Related]
9. An efficient Bayesian kinetic lumping algorithm to identify metastable conformational states via Gibbs sampling.
Wang W; Liang T; Sheong FK; Fan X; Huang X
J Chem Phys; 2018 Aug; 149(7):072337. PubMed ID: 30134698
[TBL] [Abstract][Full Text] [Related]
10. A Bayesian method for construction of Markov models to describe dynamics on various time-scales.
Rains EK; Andersen HC
J Chem Phys; 2010 Oct; 133(14):144113. PubMed ID: 20949993
[TBL] [Abstract][Full Text] [Related]
11. Effect of Clustering Algorithm on Establishing Markov State Model for Molecular Dynamics Simulations.
Li Y; Dong Z
J Chem Inf Model; 2016 Jun; 56(6):1205-15. PubMed ID: 27249546
[TBL] [Abstract][Full Text] [Related]
12. Long-time methods for molecular dynamics simulations: Markov State Models and Milestoning.
Narayan B; Yuan Y; Fathizadeh A; Elber R; Buchete NV
Prog Mol Biol Transl Sci; 2020; 170():215-237. PubMed ID: 32145946
[TBL] [Abstract][Full Text] [Related]
13. Information Bottleneck Approach for Markov Model Construction.
Wang D; Qiu Y; Beyerle ER; Huang X; Tiwary P
J Chem Theory Comput; 2024 Jun; 20(12):5352-5367. PubMed ID: 38859575
[TBL] [Abstract][Full Text] [Related]
14. Elucidating molecular mechanisms of functional conformational changes of proteins via Markov state models.
Wang X; Unarta IC; Cheung PP; Huang X
Curr Opin Struct Biol; 2021 Apr; 67():69-77. PubMed ID: 33126140
[TBL] [Abstract][Full Text] [Related]
15. On the advantages of exploiting memory in Markov state models for biomolecular dynamics.
Cao S; Montoya-Castillo A; Wang W; Markland TE; Huang X
J Chem Phys; 2020 Jul; 153(1):014105. PubMed ID: 32640825
[TBL] [Abstract][Full Text] [Related]
16. FAST Conformational Searches by Balancing Exploration/Exploitation Trade-Offs.
Zimmerman MI; Bowman GR
J Chem Theory Comput; 2015 Dec; 11(12):5747-57. PubMed ID: 26588361
[TBL] [Abstract][Full Text] [Related]
17. Markov models of molecular kinetics: generation and validation.
Prinz JH; Wu H; Sarich M; Keller B; Senne M; Held M; Chodera JD; Schütte C; Noé F
J Chem Phys; 2011 May; 134(17):174105. PubMed ID: 21548671
[TBL] [Abstract][Full Text] [Related]
18. Ward Clustering Improves Cross-Validated Markov State Models of Protein Folding.
Husic BE; Pande VS
J Chem Theory Comput; 2017 Mar; 13(3):963-967. PubMed ID: 28195713
[TBL] [Abstract][Full Text] [Related]
19. A Minimum Variance Clustering Approach Produces Robust and Interpretable Coarse-Grained Models.
Husic BE; McKiernan KA; Wayment-Steele HK; Sultan MM; Pande VS
J Chem Theory Comput; 2018 Feb; 14(2):1071-1082. PubMed ID: 29253336
[TBL] [Abstract][Full Text] [Related]
20. Tutorial on how to build non-Markovian dynamic models from molecular dynamics simulations for studying protein conformational changes.
Wu Y; Cao S; Qiu Y; Huang X
J Chem Phys; 2024 Mar; 160(12):. PubMed ID: 38516972
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
