SignalP 6.0 predicts all five types of signal peptides using protein language models

Felix Teufel, José Juan Almagro Armenteros, Alexander Rosenberg Johansen, Magnús Halldór Gíslason, Silas Irby Pihl, Konstantinos D. Tsirigos, Ole Winther, Søren Brunak, Gunnar von Heijne, Henrik Nielsen*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Signal peptides (SPs) are short amino acid sequences that control protein secretion and translocation in all living organisms. SPs can be predicted from sequence data, but existing algorithms are unable to detect all known types of SPs. We introduce SignalP 6.0, a machine learning model that detects all five SP types and is applicable to metagenomic data.
Original languageEnglish
JournalNature Biotechnology
ISSN1087-0156
DOIs
Publication statusAccepted/In press - 2022

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