PYCOEVOL - A Python Workflow to Study Protein-protein Coevolution

Fábio Madeira, Ludwig Krippahl

2012

Abstract

Protein coevolution has emerged as an important research topic. Several methods and scoring systems were developed to quantify coevolution, though the quality of the results usually depends on the completeness of the biological data. To simplify the computation of coevolution indicators from the data, we have implemented a fully integrated and automated workflow which enables efficient analysis of protein coevolution, using the Python scripting language. Pycoevol automates access to remote or local databases and third-party applications, including also data processing functions. For a given protein complex under study, Pycoevol retrieves and processes all the information needed to undergo the analysis, namely homologous sequence search, multiple sequence alignment computation and coevolution analysis, using a Mutual Information indicator. In addition, friendly output results are created, namely histograms and heatmaps of inter-protein mutual information scores, as well as lists of significant coevolving residue pairs. An illustrative example is presented. Pycoevol is platform independent, and is available under the general public license from http://code.google.com/p/pycoevol.

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Paper Citation


in Harvard Style

Madeira F. and Krippahl L. (2012). PYCOEVOL - A Python Workflow to Study Protein-protein Coevolution . In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2012) ISBN 978-989-8425-90-4, pages 143-149. DOI: 10.5220/0003737901430149


in Bibtex Style

@conference{bioinformatics12,
author={Fábio Madeira and Ludwig Krippahl},
title={PYCOEVOL - A Python Workflow to Study Protein-protein Coevolution},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2012)},
year={2012},
pages={143-149},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003737901430149},
isbn={978-989-8425-90-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2012)
TI - PYCOEVOL - A Python Workflow to Study Protein-protein Coevolution
SN - 978-989-8425-90-4
AU - Madeira F.
AU - Krippahl L.
PY - 2012
SP - 143
EP - 149
DO - 10.5220/0003737901430149