A neural network method for identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites

Int J Neural Syst. Oct-Dec 1997;8(5-6):581-99. doi: 10.1142/s0129065797000537.

Abstract

We have developed a new method for the identification of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequences. The method performs significantly better than previous prediction schemes, and can easily be applied to genome-wide data sets. Discrimination between cleaved signal peptides and uncleaved N-terminal signal-anchor sequences is also possible, though with lower precision. Predictions can be made on a publicly available WWW server: http://www.cbs.dtu.dk/services/SignalP/.

MeSH terms

  • Algorithms
  • Amino Acid Sequence
  • Computer Systems
  • Cytoplasm / chemistry
  • Databases, Factual
  • Eukaryotic Cells / physiology*
  • Genome
  • Haemophilus / genetics
  • Humans
  • Molecular Sequence Data
  • Neural Networks, Computer*
  • Nuclear Proteins / chemistry
  • Prokaryotic Cells / physiology*
  • Protein Sorting Signals / chemistry*

Substances

  • Nuclear Proteins
  • Protein Sorting Signals