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ProFeatMap: a highly customizable tool for 2D feature representation of protein sets
MOTIVATION: Studies of sets of proteins are a central point in biology. In particular, the application of omics in the last decades has generated lists of several hundreds or thousands of proteins or genes. However, these lists are often not inspected globally, possibly due to the lack of tools capa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10023195/ https://www.ncbi.nlm.nih.gov/pubmed/36936371 http://dx.doi.org/10.1093/bioadv/vbad022 |
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author | Bich, Goran Monsellier, Elodie Travé, Gilles Nominé, Yves |
author_facet | Bich, Goran Monsellier, Elodie Travé, Gilles Nominé, Yves |
author_sort | Bich, Goran |
collection | PubMed |
description | MOTIVATION: Studies of sets of proteins are a central point in biology. In particular, the application of omics in the last decades has generated lists of several hundreds or thousands of proteins or genes. However, these lists are often not inspected globally, possibly due to the lack of tools capable of simultaneously visualizing the feature architectures of a large number of proteins. RESULTS: Here, we present ProFeatMap, an intuitive Python-based website. For a given set of proteins, it allows to display features such as domains, repeats, disorder or post-translational modifications and their organization along the sequences, into a highly customizable 2D map. Starting from a user-defined protein list of UniProt accession codes, ProFeatMap extracts the most important annotated features available for each protein from one of the well-established databases such as Uniprot or InterPro, allocates shapes and colors, potentially depending on quantitative or qualitative data and sorts the protein list based on homologous feature content. The resulting publication-quality map allows even large protein families to be explored, and to classify them based on shared features. It can help to gain insights, for example, feature redundancy or feature pattern, that were previously overlooked. ProFeatMap is freely available on the web at: https://profeatmap.pythonanywhere.com/. AVAILABILITY AND IMPLEMENTATION: Source code is freely accessible at https://github.com/profeatmap/ProFeatMap under the GPL license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online. |
format | Online Article Text |
id | pubmed-10023195 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-100231952023-03-18 ProFeatMap: a highly customizable tool for 2D feature representation of protein sets Bich, Goran Monsellier, Elodie Travé, Gilles Nominé, Yves Bioinform Adv Application Note MOTIVATION: Studies of sets of proteins are a central point in biology. In particular, the application of omics in the last decades has generated lists of several hundreds or thousands of proteins or genes. However, these lists are often not inspected globally, possibly due to the lack of tools capable of simultaneously visualizing the feature architectures of a large number of proteins. RESULTS: Here, we present ProFeatMap, an intuitive Python-based website. For a given set of proteins, it allows to display features such as domains, repeats, disorder or post-translational modifications and their organization along the sequences, into a highly customizable 2D map. Starting from a user-defined protein list of UniProt accession codes, ProFeatMap extracts the most important annotated features available for each protein from one of the well-established databases such as Uniprot or InterPro, allocates shapes and colors, potentially depending on quantitative or qualitative data and sorts the protein list based on homologous feature content. The resulting publication-quality map allows even large protein families to be explored, and to classify them based on shared features. It can help to gain insights, for example, feature redundancy or feature pattern, that were previously overlooked. ProFeatMap is freely available on the web at: https://profeatmap.pythonanywhere.com/. AVAILABILITY AND IMPLEMENTATION: Source code is freely accessible at https://github.com/profeatmap/ProFeatMap under the GPL license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online. Oxford University Press 2023-03-09 /pmc/articles/PMC10023195/ /pubmed/36936371 http://dx.doi.org/10.1093/bioadv/vbad022 Text en © The Author(s) 2023. 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 (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 | Application Note Bich, Goran Monsellier, Elodie Travé, Gilles Nominé, Yves ProFeatMap: a highly customizable tool for 2D feature representation of protein sets |
title | ProFeatMap: a highly customizable tool for 2D feature representation of protein sets |
title_full | ProFeatMap: a highly customizable tool for 2D feature representation of protein sets |
title_fullStr | ProFeatMap: a highly customizable tool for 2D feature representation of protein sets |
title_full_unstemmed | ProFeatMap: a highly customizable tool for 2D feature representation of protein sets |
title_short | ProFeatMap: a highly customizable tool for 2D feature representation of protein sets |
title_sort | profeatmap: a highly customizable tool for 2d feature representation of protein sets |
topic | Application Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10023195/ https://www.ncbi.nlm.nih.gov/pubmed/36936371 http://dx.doi.org/10.1093/bioadv/vbad022 |
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