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PAFway: pairwise associations between functional annotations in biological networks and pathways

MOTIVATION: Large gene networks can be dense and difficult to interpret in a biologically meaningful way. RESULTS: Here, we introduce PAFway, which estimates pairwise associations between functional annotations in biological networks and pathways. It answers the biological question: do genes that ha...

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Detalles Bibliográficos
Autores principales: Mahjoub, Mahiar, Ezer, Daphne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7750965/
https://www.ncbi.nlm.nih.gov/pubmed/32678900
http://dx.doi.org/10.1093/bioinformatics/btaa639
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author Mahjoub, Mahiar
Ezer, Daphne
author_facet Mahjoub, Mahiar
Ezer, Daphne
author_sort Mahjoub, Mahiar
collection PubMed
description MOTIVATION: Large gene networks can be dense and difficult to interpret in a biologically meaningful way. RESULTS: Here, we introduce PAFway, which estimates pairwise associations between functional annotations in biological networks and pathways. It answers the biological question: do genes that have a specific function tend to regulate genes that have a different specific function? The results can be visualized as a heatmap or a network of biological functions. We apply this package to reveal associations between functional annotations in an Arabidopsis thaliana gene network. AVAILABILITY AND IMPLEMENTATION: PAFway is submitted to CRAN. Currently available here: https://github.com/ezer/PAFway. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-77509652020-12-28 PAFway: pairwise associations between functional annotations in biological networks and pathways Mahjoub, Mahiar Ezer, Daphne Bioinformatics Applications Notes MOTIVATION: Large gene networks can be dense and difficult to interpret in a biologically meaningful way. RESULTS: Here, we introduce PAFway, which estimates pairwise associations between functional annotations in biological networks and pathways. It answers the biological question: do genes that have a specific function tend to regulate genes that have a different specific function? The results can be visualized as a heatmap or a network of biological functions. We apply this package to reveal associations between functional annotations in an Arabidopsis thaliana gene network. AVAILABILITY AND IMPLEMENTATION: PAFway is submitted to CRAN. Currently available here: https://github.com/ezer/PAFway. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-07-17 /pmc/articles/PMC7750965/ /pubmed/32678900 http://dx.doi.org/10.1093/bioinformatics/btaa639 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Mahjoub, Mahiar
Ezer, Daphne
PAFway: pairwise associations between functional annotations in biological networks and pathways
title PAFway: pairwise associations between functional annotations in biological networks and pathways
title_full PAFway: pairwise associations between functional annotations in biological networks and pathways
title_fullStr PAFway: pairwise associations between functional annotations in biological networks and pathways
title_full_unstemmed PAFway: pairwise associations between functional annotations in biological networks and pathways
title_short PAFway: pairwise associations between functional annotations in biological networks and pathways
title_sort pafway: pairwise associations between functional annotations in biological networks and pathways
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7750965/
https://www.ncbi.nlm.nih.gov/pubmed/32678900
http://dx.doi.org/10.1093/bioinformatics/btaa639
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