Published in
Nature Research, Nature Biotechnology, 7(40), p. 1023-1025, 2022
DOI: 10.1038/s41587-021-01156-3
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SignalP 6.0 predicts all five types of signal peptides using protein language models
Journal article published in 2022 by
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
,
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
This paper is made freely available by the publisher.
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Abstract
AbstractSignal 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.