SignalP 6.0 predicts all five types of signal peptides using protein language models
Nature Biotechnology 40(7): 1023-1025
Article 2022 English
Authors
FT
Felix Teufel
JA
José Juan Almagro Armenteros
AJ
Alexander Rosenberg Johansen
Abstract
1 min read
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.
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
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