SignalP 5.0 improves signal peptide predictions using deep neural networks

Research output: Contribution to journalJournal articleCommunication

José Juan Almagro Armenteros, Konstantinos Tsirigos, Casper Kaae Sønderby, Thomas Nordahl Petersen, Ole Winther, Søren Brunak, Gunnar von Heijne, Henrik Nielsen

Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish between various types of signal peptides. We present a deep neural network-based approach that improves SP prediction across all domains of life and distinguishes between three types of prokaryotic SPs.

Original languageEnglish
JournalNature Biotechnology
Volume37
Issue number4
Pages (from-to)420-423
ISSN1087-0156
DOIs
Publication statusPublished - 18 Feb 2019

ID: 214126009