Computational study demonstrates comprehensive detection of five signal peptide types using a machine learning model, suggesting enhanced capability for analyzing metagenomic sequence data.
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.
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Teufel et al. (2022) studied this question.
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