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- Title
DeepSig: deep learning improves signal peptide detection in proteins.
- Authors
Savojardo, Castrense; Martelli, Pier Luigi; Fariselli, Piero; Casadio, Rita
- Abstract
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.
- Subjects
SIGNAL peptides; AMINO acid sequence; DEEP learning; ARTIFICIAL neural networks; BIG data
- Publication
Bioinformatics, 2018, Vol 34, Issue 10, p1690
- ISSN
1367-4803
- Publication type
Article
- DOI
10.1093/bioinformatics/btx818