Calculating mean first passage times from Markov models of proteins

Christian H. Jensen; Dmitry Nerukh; Robert C. Glen

doi:10.1063/1.2793397

Calculating mean first passage times from Markov models of proteins

Christian H. Jensen^*
, Dmitry Nerukh
, Robert C. Glen

^*Corresponding author for this work

University of Cambridge

Research output: Contribution to journal › Conference article › peer-review

2 Citations (Scopus)

536 Downloads (Pure)

Abstract

Assuming that the dynamics of peptides and proteins can be described by Markov transitions between different configurational states, we present a method which can calculate the mean first passage time (MFPT) between sets of initial and final states. The method is described in detail and differences between this and a method commonly employed [1] are explained. It is shown that the proposed method is (i) more general in allowing sets of final states, (ii) significantly faster, (iii) more accurate since it does not involve the calculation of infinite summations. Particular attention is given to the biologically important case of multiple final states.

Original language	English
Pages (from-to)	150-157
Number of pages	8
Journal	AIP Conference Proceedings
Volume	940
DOIs	https://doi.org/10.1063/1.2793397
Publication status	Published - 1 Dec 2007
Event	3rd International Symposium on Computational Life Science, CompLife 2007 - Utrecht, Netherlands Duration: 4 Oct 2007 → 5 Oct 2007

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10.1063/1.2793397

Calculating Mean First Passage Times from Markov Models of Proteins
Copyright © 2007, AIP Publishing. AIP Conference Proceedings 940, 150 (2007); doi: 10.1063/1.2793397
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abstract = "Assuming that the dynamics of peptides and proteins can be described by Markov transitions between different configurational states, we present a method which can calculate the mean first passage time (MFPT) between sets of initial and final states. The method is described in detail and differences between this and a method commonly employed [1] are explained. It is shown that the proposed method is (i) more general in allowing sets of final states, (ii) significantly faster, (iii) more accurate since it does not involve the calculation of infinite summations. Particular attention is given to the biologically important case of multiple final states.",

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note = "Copyright {\textcopyright} 2007, AIP Publishing. AIP Conference Proceedings 940, 150 (2007); doi: 10.1063/1.2793397; 3rd International Symposium on Computational Life Science, CompLife 2007 ; Conference date: 04-10-2007 Through 05-10-2007",

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T1 - Calculating mean first passage times from Markov models of proteins

AU - Jensen, Christian H.

AU - Nerukh, Dmitry

AU - Glen, Robert C.

PY - 2007/12/1

Y1 - 2007/12/1

N2 - Assuming that the dynamics of peptides and proteins can be described by Markov transitions between different configurational states, we present a method which can calculate the mean first passage time (MFPT) between sets of initial and final states. The method is described in detail and differences between this and a method commonly employed [1] are explained. It is shown that the proposed method is (i) more general in allowing sets of final states, (ii) significantly faster, (iii) more accurate since it does not involve the calculation of infinite summations. Particular attention is given to the biologically important case of multiple final states.

AB - Assuming that the dynamics of peptides and proteins can be described by Markov transitions between different configurational states, we present a method which can calculate the mean first passage time (MFPT) between sets of initial and final states. The method is described in detail and differences between this and a method commonly employed [1] are explained. It is shown that the proposed method is (i) more general in allowing sets of final states, (ii) significantly faster, (iii) more accurate since it does not involve the calculation of infinite summations. Particular attention is given to the biologically important case of multiple final states.

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U2 - 10.1063/1.2793397

DO - 10.1063/1.2793397

M3 - Conference article

AN - SCOPUS:40249110162

SN - 0094-243X

VL - 940

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EP - 157

JO - AIP Conference Proceedings

JF - AIP Conference Proceedings

T2 - 3rd International Symposium on Computational Life Science, CompLife 2007

Y2 - 4 October 2007 through 5 October 2007

ER -

Calculating mean first passage times from Markov models of proteins

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