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Path2PPI: an R package to predict protein–protein interaction networks for a set of proteins

Summary: We introduce Path2PPI, a new R package to identify protein–protein interaction (PPI) networks for fully sequenced organisms for which nearly none PPI are known. Path2PPI predicts PPI networks based on sets of proteins from well-established model organisms, providing an intuitive visualizati...

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Detalles Bibliográficos
Autores principales: Philipp, Oliver, Osiewacz, Heinz D., Koch, Ina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4848400/
https://www.ncbi.nlm.nih.gov/pubmed/26733452
http://dx.doi.org/10.1093/bioinformatics/btv765
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author Philipp, Oliver
Osiewacz, Heinz D.
Koch, Ina
author_facet Philipp, Oliver
Osiewacz, Heinz D.
Koch, Ina
author_sort Philipp, Oliver
collection PubMed
description Summary: We introduce Path2PPI, a new R package to identify protein–protein interaction (PPI) networks for fully sequenced organisms for which nearly none PPI are known. Path2PPI predicts PPI networks based on sets of proteins from well-established model organisms, providing an intuitive visualization and usability. It can be used to combine and transfer information of a certain pathway or biological process from several reference organisms to one target organism. Availability and implementation: Path2PPI is an open-source tool implemented in R. It can be obtained from the Bioconductor project: http://bioconductor.org/packages/Path2PPI/ Contact: ina.koch@bioinformatik.uni-frankfurt.de Supplementary information: Supplementary data are available at Bioinformatics online.
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spelling pubmed-48484002016-04-29 Path2PPI: an R package to predict protein–protein interaction networks for a set of proteins Philipp, Oliver Osiewacz, Heinz D. Koch, Ina Bioinformatics Applications Notes Summary: We introduce Path2PPI, a new R package to identify protein–protein interaction (PPI) networks for fully sequenced organisms for which nearly none PPI are known. Path2PPI predicts PPI networks based on sets of proteins from well-established model organisms, providing an intuitive visualization and usability. It can be used to combine and transfer information of a certain pathway or biological process from several reference organisms to one target organism. Availability and implementation: Path2PPI is an open-source tool implemented in R. It can be obtained from the Bioconductor project: http://bioconductor.org/packages/Path2PPI/ Contact: ina.koch@bioinformatik.uni-frankfurt.de Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2016-05-01 2016-01-05 /pmc/articles/PMC4848400/ /pubmed/26733452 http://dx.doi.org/10.1093/bioinformatics/btv765 Text en © The Author 2016. 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
Philipp, Oliver
Osiewacz, Heinz D.
Koch, Ina
Path2PPI: an R package to predict protein–protein interaction networks for a set of proteins
title Path2PPI: an R package to predict protein–protein interaction networks for a set of proteins
title_full Path2PPI: an R package to predict protein–protein interaction networks for a set of proteins
title_fullStr Path2PPI: an R package to predict protein–protein interaction networks for a set of proteins
title_full_unstemmed Path2PPI: an R package to predict protein–protein interaction networks for a set of proteins
title_short Path2PPI: an R package to predict protein–protein interaction networks for a set of proteins
title_sort path2ppi: an r package to predict protein–protein interaction networks for a set of proteins
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4848400/
https://www.ncbi.nlm.nih.gov/pubmed/26733452
http://dx.doi.org/10.1093/bioinformatics/btv765
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