Nucleic Acids Research, Vol 26, Issue 9 2230-2236, Copyright © 1998 by Oxford University Press
A Reinhardt and T Hubbard
Neural networks have been trained to predict the subcellular location of
proteins in prokaryotic or eukaryotic cells from their amino acid
composition. For three possible subcellular locations in prokaryotic
organisms a prediction accuracy of 81% can be achieved. Assigning a
reliability index, 33% of the predictions can be made with an accuracy of
91%. For eukaryotic proteins (excluding plant sequences) an overall
prediction accuracy of 66% for four locations was achieved, with 33% of the
sequences being predicted with an accuracy of 82% or better. With the
subcellular location restricting a protein's possible function, this method
should be a useful tool for the systematic analysis of genome data and is
available via a server on the world wide web.
ARTICLES
Using neural networks for prediction of the subcellular location of proteins
The Sanger Centre, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK. areinha@sanger.ac.uk
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