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PHAISTOS: A framework for Markov chain Monte Carlo simulation and inference of protein structure.

Boomsma, Wouter LU ; Frellsen, Jes; Harder, Tim; Bottaro, Sandro; Johansson, Kristoffer E; Tian, Pengfei; Stovgaard, Kasper; Andreetta, Christian; Olsson, Simon and Valentin, Jan B, et al. (2013) In Journal of Computational Chemistry 34(19). p.1697-1705
Abstract
We present a new software framework for Markov chain Monte Carlo sampling for simulation, prediction, and inference of protein structure. The software package contains implementations of recent advances in Monte Carlo methodology, such as efficient local updates and sampling from probabilistic models of local protein structure. These models form a probabilistic alternative to the widely used fragment and rotamer libraries. Combined with an easily extendible software architecture, this makes PHAISTOS well suited for Bayesian inference of protein structure from sequence and/or experimental data. Currently, two force-fields are available within the framework: PROFASI and OPLS-AA/L, the latter including the generalized Born surface area... (More)
We present a new software framework for Markov chain Monte Carlo sampling for simulation, prediction, and inference of protein structure. The software package contains implementations of recent advances in Monte Carlo methodology, such as efficient local updates and sampling from probabilistic models of local protein structure. These models form a probabilistic alternative to the widely used fragment and rotamer libraries. Combined with an easily extendible software architecture, this makes PHAISTOS well suited for Bayesian inference of protein structure from sequence and/or experimental data. Currently, two force-fields are available within the framework: PROFASI and OPLS-AA/L, the latter including the generalized Born surface area solvent model. A flexible command-line and configuration-file interface allows users quickly to set up simulations with the desired configuration. PHAISTOS is released under the GNU General Public License v3.0. Source code and documentation are freely available from http://phaistos.sourceforge.net. The software is implemented in C++ and has been tested on Linux and OSX platforms. © 2013 Wiley Periodicals, Inc. (Less)
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Contribution to journal
publication status
published
subject
in
Journal of Computational Chemistry
volume
34
issue
19
pages
1697 - 1705
publisher
John Wiley & Sons
external identifiers
  • wos:000320389700008
  • pmid:23619610
  • scopus:84879115316
ISSN
1096-987X
DOI
10.1002/jcc.23292
language
English
LU publication?
yes
id
73c501c5-3224-4043-b2aa-4ee81ec15c3c (old id 3733331)
date added to LUP
2013-05-06 17:12:09
date last changed
2019-08-07 01:26:04
@article{73c501c5-3224-4043-b2aa-4ee81ec15c3c,
  abstract     = {We present a new software framework for Markov chain Monte Carlo sampling for simulation, prediction, and inference of protein structure. The software package contains implementations of recent advances in Monte Carlo methodology, such as efficient local updates and sampling from probabilistic models of local protein structure. These models form a probabilistic alternative to the widely used fragment and rotamer libraries. Combined with an easily extendible software architecture, this makes PHAISTOS well suited for Bayesian inference of protein structure from sequence and/or experimental data. Currently, two force-fields are available within the framework: PROFASI and OPLS-AA/L, the latter including the generalized Born surface area solvent model. A flexible command-line and configuration-file interface allows users quickly to set up simulations with the desired configuration. PHAISTOS is released under the GNU General Public License v3.0. Source code and documentation are freely available from http://phaistos.sourceforge.net. The software is implemented in C++ and has been tested on Linux and OSX platforms. © 2013 Wiley Periodicals, Inc.},
  author       = {Boomsma, Wouter and Frellsen, Jes and Harder, Tim and Bottaro, Sandro and Johansson, Kristoffer E and Tian, Pengfei and Stovgaard, Kasper and Andreetta, Christian and Olsson, Simon and Valentin, Jan B and Antonov, Lubomir D and Christensen, Anders S and Borg, Mikael and Jensen, Jan H and Lindorff-Larsen, Kresten and Ferkinghoff-Borg, Jesper and Hamelryck, Thomas},
  issn         = {1096-987X},
  language     = {eng},
  number       = {19},
  pages        = {1697--1705},
  publisher    = {John Wiley & Sons},
  series       = {Journal of Computational Chemistry},
  title        = {PHAISTOS: A framework for Markov chain Monte Carlo simulation and inference of protein structure.},
  url          = {http://dx.doi.org/10.1002/jcc.23292},
  volume       = {34},
  year         = {2013},
}