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PANADA: Protein Association Network Annotation, Determination and Analysis

Increasingly large numbers of proteins require methods for functional annotation. This is typically based on pairwise inference from the homology of either protein sequence or structure. Recently, similarity networks have been presented to leverage both the ability to visualize relationships between...

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Detalles Bibliográficos
Autores principales: Martin, Alberto J. M., Walsh, Ian, Domenico, Tomás Di, Mičetić, Ivan, Tosatto, Silvio C. E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3827049/
https://www.ncbi.nlm.nih.gov/pubmed/24265686
http://dx.doi.org/10.1371/journal.pone.0078383
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author Martin, Alberto J. M.
Walsh, Ian
Domenico, Tomás Di
Mičetić, Ivan
Tosatto, Silvio C. E.
author_facet Martin, Alberto J. M.
Walsh, Ian
Domenico, Tomás Di
Mičetić, Ivan
Tosatto, Silvio C. E.
author_sort Martin, Alberto J. M.
collection PubMed
description Increasingly large numbers of proteins require methods for functional annotation. This is typically based on pairwise inference from the homology of either protein sequence or structure. Recently, similarity networks have been presented to leverage both the ability to visualize relationships between proteins and assess the transferability of functional inference. Here we present PANADA, a novel toolkit for the visualization and analysis of protein similarity networks in Cytoscape. Networks can be constructed based on pairwise sequence or structural alignments either on a set of proteins or, alternatively, by database search from a single sequence. The Panada web server, executable for download and examples and extensive help files are available at URL: http://protein.bio.unipd.it/panada/.
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spelling pubmed-38270492013-11-21 PANADA: Protein Association Network Annotation, Determination and Analysis Martin, Alberto J. M. Walsh, Ian Domenico, Tomás Di Mičetić, Ivan Tosatto, Silvio C. E. PLoS One Research Article Increasingly large numbers of proteins require methods for functional annotation. This is typically based on pairwise inference from the homology of either protein sequence or structure. Recently, similarity networks have been presented to leverage both the ability to visualize relationships between proteins and assess the transferability of functional inference. Here we present PANADA, a novel toolkit for the visualization and analysis of protein similarity networks in Cytoscape. Networks can be constructed based on pairwise sequence or structural alignments either on a set of proteins or, alternatively, by database search from a single sequence. The Panada web server, executable for download and examples and extensive help files are available at URL: http://protein.bio.unipd.it/panada/. Public Library of Science 2013-11-12 /pmc/articles/PMC3827049/ /pubmed/24265686 http://dx.doi.org/10.1371/journal.pone.0078383 Text en © 2013 Martin et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Martin, Alberto J. M.
Walsh, Ian
Domenico, Tomás Di
Mičetić, Ivan
Tosatto, Silvio C. E.
PANADA: Protein Association Network Annotation, Determination and Analysis
title PANADA: Protein Association Network Annotation, Determination and Analysis
title_full PANADA: Protein Association Network Annotation, Determination and Analysis
title_fullStr PANADA: Protein Association Network Annotation, Determination and Analysis
title_full_unstemmed PANADA: Protein Association Network Annotation, Determination and Analysis
title_short PANADA: Protein Association Network Annotation, Determination and Analysis
title_sort panada: protein association network annotation, determination and analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3827049/
https://www.ncbi.nlm.nih.gov/pubmed/24265686
http://dx.doi.org/10.1371/journal.pone.0078383
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