SignalP 5.0 improves signal peptide predictions using deep neural networks

José Juan Almagro Armenteros, Konstantinos D Tsirigos, Casper Kaae Sønderby, Thomas Nordahl Petersen, Ole Winther, Søren Brunak, Gunnar von Heijne, Henrik Nielsen

2948 Citations (Scopus)

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.

Original languageEnglish
JournalNature Biotechnology
Volume37
Issue number4
Pages (from-to)420-423
Number of pages4
ISSN1087-0156
DOIs
Publication statusPublished - Apr 2019
Externally publishedYes

Keywords

  • Algorithms
  • Amino Acid Sequence
  • Archaeal Proteins/classification
  • Bacterial Proteins/classification
  • Biotechnology
  • Computational Biology
  • Eukaryota/genetics
  • Neural Networks, Computer
  • Protein Sorting Signals/genetics
  • Sequence Analysis, Protein
  • Software

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