Using Stochastic Roadmap Simulation to Predict Experimental Quantities in Protein Folding Kinetics: Folding Rates and Phi-Values-Reference-Cited by-同舟云学术

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Using Stochastic Roadmap Simulation to Predict Experimental Quantities in Protein Folding Kinetics: Folding Rates and Phi-Values

Published:2007-06 Issue:5 Volume:14 Page:578-593
ISSN:1066-5277
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Chiang Tsung-Han¹,Apaydin Mehmet Serkan²,Brutlag Douglas L.³,Hsu David¹,Latombe Jean-Claude⁴

Affiliation:

1. School of Computing, National University of Singapore, Singapore.

2. Department of Computer Science, Duke University, Durham, North Carolina.

3. Department of Biochemistry, Stanford University, Stanford, California.

4. Department of Computer Science, Stanford University, Stanford, California.

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modeling and Simulation

Link

http://www.liebertpub.com/doi/pdf/10.1089/cmb.2007.R004

Reference31 articles.

1. Prediction of protein-folding mechanisms from free-energy landscapes derived from native structures

2. Using motion planning to map protein folding landscapes and analyze folding kinetics of known native structures

3. Stochastic roadmap simulation

4. A surprising simplicity to protein folding

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1. Structure of the Singular Manifold of Protein Backbone and Its Applications;IEEE Access;2020

2. Sample-Based Models of Protein Energy Landscapes and Slow Structural Rearrangements;Journal of Computational Biology;2018-01

3. Frustration-guided motion planning reveals conformational transitions in proteins;Proteins: Structure, Function, and Bioinformatics;2017-07-12

4. A Survey of Computational Treatments of Biomolecules by Robotics-Inspired Methods Modeling Equilibrium Structure and Dynamic;Journal of Artificial Intelligence Research;2016-11-29

5. Sample-based Models of Protein Structural Transitions;Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics;2016-10-02

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