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DeepSig: deep learning improves signal peptide detection in proteins

DeepSig: deep learning improves signal peptide detection in proteins MotivationThe identification of signal peptides in protein sequences is an important step toward protein localization and function characterization.ResultsHere, 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 implementationDeepSig 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 informationSupplementary data are available at Bioinformatics online. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bioinformatics Oxford University Press

DeepSig: deep learning improves signal peptide detection in proteins

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Publisher
Oxford University Press
Copyright
© The Author(s) 2017. Published by Oxford University Press.
ISSN
1367-4803
eISSN
1460-2059
DOI
10.1093/bioinformatics/btx818
Publisher site
See Article on Publisher Site

Abstract

MotivationThe identification of signal peptides in protein sequences is an important step toward protein localization and function characterization.ResultsHere, 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 implementationDeepSig 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 informationSupplementary data are available at Bioinformatics online.

Journal

BioinformaticsOxford University Press

Published: May 15, 2018

References