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SignalP 5.0 improves signal peptide predictions using deep neural networks
José Juan Almagro Armenteros1, Konstantinos D Tsirigos1,2,3,4, Casper Kaae Sønderby5
1Department of Bio and Health Informatics, Technical University of Denmark, Kgs Lyngby, Denmark.
Abstract:
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.
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