کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10826079 | 1064709 | 2010 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Everything you wanted to know about Markov State Models but were afraid to ask
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
بیوشیمی، ژنتیک و زیست شناسی مولکولی
زیست شیمی
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چکیده انگلیسی
Simulating protein folding has been a challenging problem for decades due to the long timescales involved (compared with what is possible to simulate) and the challenges of gaining insight from the complex nature of the resulting simulation data. Markov State Models (MSMs) present a means to tackle both of these challenges, yielding simulations on experimentally relevant timescales, statistical significance, and coarse grained representations that are readily humanly understandable. Here, we review this method with the intended audience of non-experts, in order to introduce the method to a broader audience. We review the motivations, methods, and caveats of MSMs, as well as some recent highlights of applications of the method. We conclude by discussing how this approach is part of a paradigm shift in how one uses simulations, away from anecdotal single-trajectory approaches to a more comprehensive statistical approach.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Methods - Volume 52, Issue 1, September 2010, Pages 99-105
Journal: Methods - Volume 52, Issue 1, September 2010, Pages 99-105
نویسندگان
Vijay S. Pande, Kyle Beauchamp, Gregory R. Bowman,