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Open Access Method

ngLOC: an n-gram-based Bayesian method for estimating the subcellular proteomes of eukaryotes

Brian R King12 and Chittibabu Guda23*

Author affiliations

1 Department of Computer Science, State University of New York at Albany, Washington Ave, Albany, New York 12222, USA

2 Gen*NY*sis Center for Excellence in Cancer Genomics, State University of New York at Albany, Discovery Drive, Rensselaer, New York 12144-3456, USA

3 Department of Epidemiology and Biostatistics, State University of New York at Albany, Discovery Drive, Rensselaer, New York 12144-3456, USA

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Citation and License

Genome Biology 2007, 8:R68  doi:10.1186/gb-2007-8-5-r68

Published: 1 May 2007

Abstract

We present a method called ngLOC, an n-gram-based Bayesian classifier that predicts the localization of a protein sequence over ten distinct subcellular organelles. A tenfold cross-validation result shows an accuracy of 89% for sequences localized to a single organelle, and 82% for those localized to multiple organelles. An enhanced version of ngLOC was developed to estimate the subcellular proteomes of eight eukaryotic organisms: yeast, nematode, fruitfly, mosquito, zebrafish, chicken, mouse, and human.