%0 Journal Article %1 McGibbon2015mdtraj %A McGibbon, Robert T. %A Beauchamp, Kyle A. %A Harrigan, Matthew P. %A Klein, Christoph %A Swails, Jason M. %A Hernández, Carlos X. %A Schwantes, Christian R. %A Wang, Lee-Ping %A Lane, Thomas J. %A Pande, Vijay S. %D 2015 %J Biophysical Journal %K molecular-dynamics python software trajectory-analysis %N 8 %P 1528 - 1532 %R http://dx.doi.org/10.1016/j.bpj.2015.08.015 %T MDTraj: A Modern Open Library for the Analysis of Molecular Dynamics Trajectories %U http://www.sciencedirect.com/science/article/pii/S0006349515008267 %V 109 %X Abstract As molecular dynamics (MD) simulations continue to evolve into powerful computational tools for studying complex biomolecular systems, the necessity of flexible and easy-to-use software tools for the analysis of these simulations is growing. We have developed MDTraj, a modern, lightweight, and fast software package for analyzing \MD\ simulations. \MDTraj\ reads and writes trajectory data in a wide variety of commonly used formats. It provides a large number of trajectory analysis capabilities including minimal root-mean-square-deviation calculations, secondary structure assignment, and the extraction of common order parameters. The package has a strong focus on interoperability with the wider scientific Python ecosystem, bridging the gap between \MD\ data and the rapidly growing collection of industry-standard statistical analysis and visualization tools in Python. \MDTraj\ is a powerful and user-friendly software package that simplifies the analysis of \MD\ data and connects these datasets with the modern interactive data science software ecosystem in Python.

@article{McGibbon2015mdtraj, abstract = {Abstract As molecular dynamics (MD) simulations continue to evolve into powerful computational tools for studying complex biomolecular systems, the necessity of flexible and easy-to-use software tools for the analysis of these simulations is growing. We have developed MDTraj, a modern, lightweight, and fast software package for analyzing \{MD\} simulations. \{MDTraj\} reads and writes trajectory data in a wide variety of commonly used formats. It provides a large number of trajectory analysis capabilities including minimal root-mean-square-deviation calculations, secondary structure assignment, and the extraction of common order parameters. The package has a strong focus on interoperability with the wider scientific Python ecosystem, bridging the gap between \{MD\} data and the rapidly growing collection of industry-standard statistical analysis and visualization tools in Python. \{MDTraj\} is a powerful and user-friendly software package that simplifies the analysis of \{MD\} data and connects these datasets with the modern interactive data science software ecosystem in Python. }, added-at = {2016-09-28T21:21:48.000+0200}, author = {McGibbon, Robert T. and Beauchamp, Kyle A. and Harrigan, Matthew P. and Klein, Christoph and Swails, Jason M. and Hernández, Carlos X. and Schwantes, Christian R. and Wang, Lee-Ping and Lane, Thomas J. and Pande, Vijay S.}, biburl = {https://www.bibsonomy.org/bibtex/22135c61993c8890166eca99310d4300b/salotz}, description = {MDTraj: A Modern Open Library for the Analysis of Molecular Dynamics Trajectories}, doi = {http://dx.doi.org/10.1016/j.bpj.2015.08.015}, interhash = {840a93815291bff94ed54d2c504c5315}, intrahash = {2135c61993c8890166eca99310d4300b}, issn = {0006-3495}, journal = {Biophysical Journal }, keywords = {molecular-dynamics python software trajectory-analysis}, number = 8, pages = {1528 - 1532}, timestamp = {2016-09-28T21:21:48.000+0200}, title = {MDTraj: A Modern Open Library for the Analysis of Molecular Dynamics Trajectories }, url = {http://www.sciencedirect.com/science/article/pii/S0006349515008267}, volume = 109, year = 2015 }