TY - JOUR
T1 - PyRosetta
T2 - A script-based interface for implementing molecular modeling algorithms using Rosetta
AU - Chaudhury, Sidhartha
AU - Lyskov, Sergey
AU - Gray, Jeffrey J.
N1 - Funding Information:
Funding: PyRosetta was funded through National Institute of Health (R01-GM73151 and R01-GM078221); National Science Foundation CAREER Grant CBET (0846324).
PY - 2010/1/7
Y1 - 2010/1/7
N2 - PyRosetta is a stand-alone Python-based imple-mentation of the Rosetta molecular modeling package that allows users to write custom structure prediction and design algorithms using the major Rosetta sampling and scoring functions. PyRosetta contains Python bindings to libraries that define Rosetta functions including those for accessing and manipulating protein structure, calculating energies and running Monte Carlo-based simulations. PyRosetta can be used in two ways: (i) interactively, using iPython and (ii) script-based, using Python scripting. Interactive mode contains a number of help features and is ideal for beginners while script-mode is best suited for algorithm development. PyRosetta has similar computational performance to Rosetta, can be easily scaled up for cluster applications and has been implemented for algorithms demonstrating protein docking, protein folding, loop modeling and design. Availability: PyRosetta is a stand-alone package available at http://www.pyrosetta.org under the Rosetta license which is free for academic and non-profit users. A tutorial, user's manual and sample scripts demonstrating usage are also available on the web site. Contact: pyrosetta@graylab.jhu.edu
AB - PyRosetta is a stand-alone Python-based imple-mentation of the Rosetta molecular modeling package that allows users to write custom structure prediction and design algorithms using the major Rosetta sampling and scoring functions. PyRosetta contains Python bindings to libraries that define Rosetta functions including those for accessing and manipulating protein structure, calculating energies and running Monte Carlo-based simulations. PyRosetta can be used in two ways: (i) interactively, using iPython and (ii) script-based, using Python scripting. Interactive mode contains a number of help features and is ideal for beginners while script-mode is best suited for algorithm development. PyRosetta has similar computational performance to Rosetta, can be easily scaled up for cluster applications and has been implemented for algorithms demonstrating protein docking, protein folding, loop modeling and design. Availability: PyRosetta is a stand-alone package available at http://www.pyrosetta.org under the Rosetta license which is free for academic and non-profit users. A tutorial, user's manual and sample scripts demonstrating usage are also available on the web site. Contact: pyrosetta@graylab.jhu.edu
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U2 - 10.1093/bioinformatics/btq007
DO - 10.1093/bioinformatics/btq007
M3 - Comment/debate
C2 - 20061306
AN - SCOPUS:77949617607
SN - 1367-4803
VL - 26
SP - 689
EP - 691
JO - Bioinformatics
JF - Bioinformatics
IS - 5
M1 - btq007
ER -