alexa Using neural networks for prediction of the subcellular location of proteins
Biomedical Sciences

Biomedical Sciences

International Journal of Biomedical Data Mining

Author(s): A Reinhardt, T Hubbard

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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.

This article was published in Nucleic Acid Research and referenced in International Journal of Biomedical Data Mining

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