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The EVcouplings Python framework for coevolutionary sequence analysis

SUMMARY: Coevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. We present the EVcouplings framework, a fully integrated open-source application and Python package for coevolutionary analysis...

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Autores principales: Hopf, Thomas A, Green, Anna G, Schubert, Benjamin, Mersmann, Sophia, Schärfe, Charlotta P I, Ingraham, John B, Toth-Petroczy, Agnes, Brock, Kelly, Riesselman, Adam J, Palmedo, Perry, Kang, Chan, Sheridan, Robert, Draizen, Eli J, Dallago, Christian, Sander, Chris, Marks, Debora S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499242/
https://www.ncbi.nlm.nih.gov/pubmed/30304492
http://dx.doi.org/10.1093/bioinformatics/bty862
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author Hopf, Thomas A
Green, Anna G
Schubert, Benjamin
Mersmann, Sophia
Schärfe, Charlotta P I
Ingraham, John B
Toth-Petroczy, Agnes
Brock, Kelly
Riesselman, Adam J
Palmedo, Perry
Kang, Chan
Sheridan, Robert
Draizen, Eli J
Dallago, Christian
Sander, Chris
Marks, Debora S
author_facet Hopf, Thomas A
Green, Anna G
Schubert, Benjamin
Mersmann, Sophia
Schärfe, Charlotta P I
Ingraham, John B
Toth-Petroczy, Agnes
Brock, Kelly
Riesselman, Adam J
Palmedo, Perry
Kang, Chan
Sheridan, Robert
Draizen, Eli J
Dallago, Christian
Sander, Chris
Marks, Debora S
author_sort Hopf, Thomas A
collection PubMed
description SUMMARY: Coevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. We present the EVcouplings framework, a fully integrated open-source application and Python package for coevolutionary analysis. The framework enables generation of sequence alignments, calculation and evaluation of evolutionary couplings (ECs), and de novo prediction of structure and mutation effects. The combination of an easy to use, flexible command line interface and an underlying modular Python package makes the full power of coevolutionary analyses available to entry-level and advanced users. AVAILABILITY AND IMPLEMENTATION: https://github.com/debbiemarkslab/evcouplings
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spelling pubmed-64992422019-05-07 The EVcouplings Python framework for coevolutionary sequence analysis Hopf, Thomas A Green, Anna G Schubert, Benjamin Mersmann, Sophia Schärfe, Charlotta P I Ingraham, John B Toth-Petroczy, Agnes Brock, Kelly Riesselman, Adam J Palmedo, Perry Kang, Chan Sheridan, Robert Draizen, Eli J Dallago, Christian Sander, Chris Marks, Debora S Bioinformatics Applications Notes SUMMARY: Coevolutionary sequence analysis has become a commonly used technique for de novo prediction of the structure and function of proteins, RNA, and protein complexes. We present the EVcouplings framework, a fully integrated open-source application and Python package for coevolutionary analysis. The framework enables generation of sequence alignments, calculation and evaluation of evolutionary couplings (ECs), and de novo prediction of structure and mutation effects. The combination of an easy to use, flexible command line interface and an underlying modular Python package makes the full power of coevolutionary analyses available to entry-level and advanced users. AVAILABILITY AND IMPLEMENTATION: https://github.com/debbiemarkslab/evcouplings Oxford University Press 2019-05-01 2018-10-09 /pmc/articles/PMC6499242/ /pubmed/30304492 http://dx.doi.org/10.1093/bioinformatics/bty862 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Applications Notes
Hopf, Thomas A
Green, Anna G
Schubert, Benjamin
Mersmann, Sophia
Schärfe, Charlotta P I
Ingraham, John B
Toth-Petroczy, Agnes
Brock, Kelly
Riesselman, Adam J
Palmedo, Perry
Kang, Chan
Sheridan, Robert
Draizen, Eli J
Dallago, Christian
Sander, Chris
Marks, Debora S
The EVcouplings Python framework for coevolutionary sequence analysis
title The EVcouplings Python framework for coevolutionary sequence analysis
title_full The EVcouplings Python framework for coevolutionary sequence analysis
title_fullStr The EVcouplings Python framework for coevolutionary sequence analysis
title_full_unstemmed The EVcouplings Python framework for coevolutionary sequence analysis
title_short The EVcouplings Python framework for coevolutionary sequence analysis
title_sort evcouplings python framework for coevolutionary sequence analysis
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499242/
https://www.ncbi.nlm.nih.gov/pubmed/30304492
http://dx.doi.org/10.1093/bioinformatics/bty862
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