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DeepSig: deep learning improves signal peptide detection in proteins

MOTIVATION: The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. RESULTS: Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Com...

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Detalles Bibliográficos
Autores principales: Savojardo, Castrense, Martelli, Pier Luigi, Fariselli, Piero, Casadio, Rita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5946842/
https://www.ncbi.nlm.nih.gov/pubmed/29280997
http://dx.doi.org/10.1093/bioinformatics/btx818
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author Savojardo, Castrense
Martelli, Pier Luigi
Fariselli, Piero
Casadio, Rita
author_facet Savojardo, Castrense
Martelli, Pier Luigi
Fariselli, Piero
Casadio, Rita
author_sort Savojardo, Castrense
collection PubMed
description MOTIVATION: The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. RESULTS: Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. AVAILABILITY AND IMPLEMENTATION: DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-59468422018-05-16 DeepSig: deep learning improves signal peptide detection in proteins Savojardo, Castrense Martelli, Pier Luigi Fariselli, Piero Casadio, Rita Bioinformatics Original Papers MOTIVATION: The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. RESULTS: Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. AVAILABILITY AND IMPLEMENTATION: DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2018-05-15 2017-12-21 /pmc/articles/PMC5946842/ /pubmed/29280997 http://dx.doi.org/10.1093/bioinformatics/btx818 Text en © The Author(s) 2017. 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 Original Papers
Savojardo, Castrense
Martelli, Pier Luigi
Fariselli, Piero
Casadio, Rita
DeepSig: deep learning improves signal peptide detection in proteins
title DeepSig: deep learning improves signal peptide detection in proteins
title_full DeepSig: deep learning improves signal peptide detection in proteins
title_fullStr DeepSig: deep learning improves signal peptide detection in proteins
title_full_unstemmed DeepSig: deep learning improves signal peptide detection in proteins
title_short DeepSig: deep learning improves signal peptide detection in proteins
title_sort deepsig: deep learning improves signal peptide detection in proteins
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5946842/
https://www.ncbi.nlm.nih.gov/pubmed/29280997
http://dx.doi.org/10.1093/bioinformatics/btx818
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