Briefings in Functional Genomics and Proteomics Advance Access originally published online on February 18, 2008
Briefings in Functional Genomics and Proteomics 2008 7(1):63-73; doi:10.1093/bfgp/eln003
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The prediction of protein subcellular localization from sequence: a shortcut to functional genome annotation
Corresponding author. Rita Casadio, Biocomputing Group, Department of Biology, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. Tel: +39 051 2091284; Fax: +39 051 242576; E-mail: casadio{at}alma.unibo.it
Automated sequence annotation is a major goal of post-genomic era with hundreds of genomes in the databases, from both prokaryotes and eukaryotes. While the number of fully sequenced chromosomes from microbial organisms exponentially increased in the last decade above 600, presently we know the whole DNA content of only 25 eukaryotic organisms, including Homo sapiens. However, the process of genome annotation is far from being completed. This is particularly relevant in eukaryotes, whose cells contain several subcellular compartments, or organelles, enclosed by membranes, where different relevant functions are performed. Translocation across the membrane into the organelles is a highly regulated and complex cellular process. Indeed different proteins and/or protein isoforms, originated from genes by alternative splicing, may be conveyed to different cell compartments, depending on their specific role in the cell. During recent years the prediction of subcellular localization (SL) by computational means has been an active research area. Several methods are presently available based on different notions and addressing different aspects of SL. This review provides a short overview of the most well performing methods described in the literature, highlighting their predictive capabilities and different applications.
Keywords: subcellular localization, functional genomics, machine learning, proteome annotation, sequence-based predictions