Skip Navigation

Bioinformatics 2006 22(14):e408-e416; doi:10.1093/bioinformatics/btl222
This Article
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Google Scholar
Right arrow Articles by Pierleoni, A.
Right arrow Articles by Casadio, R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Pierleoni, A.
Right arrow Articles by Casadio, R.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

BaCelLo: a balanced subcellular localization predictor

Andrea Pierleoni , Pier Luigi Martelli , Piero Fariselli and Rita Casadio *

Biocomputing Group, Dept. of Biology University of Bologna via Irnerio 42, 40126 Bologna, Italy

*To whom correspondence should be addressed.

Motivation. The knowledge of the subcellular localization of a protein is fundamental for elucidating its function. It is difficult to determine the subcellular location for eukaryotic cells with experimental high-throughput procedures. Computational procedures are then needed for annotating the subcellular location of proteins in large scale genomic projects.

Results. BaCelLo is a predictor for five classes of subcellular localization (secretory pathway, cytoplasm, nucleus, mitochondrion and chloroplast) and it is based on different SVMs organized in a decision tree. The system exploits the information derived from the residue sequence and from the evolutionary information contained in alignment profiles. It analyzes the whole sequence composition and the compositions of both the N- and C-termini. The training set is curated in order to avoid redundancy. For the first time a balancing procedure is introduced in order to mitigate the effect of biased training sets. Three kingdom-specific predictors are implemented: for animals, plants and fungi, respectively. When distributing the proteins from animals and fungi into four classes, accuracy of BaCelLo reach 74% and 76%, respectively; a score of 67% is obtained when proteins from plants are distributed into five classes. BaCelLo outperforms the other presently available methods for the same task and gives more balanced accuracy and coverage values for each class. We also predict the subcellular localization of five whole proteomes, Homo sapiens, Mus musculus, Caenorhabditis elegans, Saccharomyces cerevisiae and Arabidopsis thaliana, comparing the protein content in each different compartment.

Availability. BaCelLo can be accessed at http://www.biocomp.unibo.it/bacello/

Contact. casadio{at}alma.unibo.it, andrea{at}biocomp.unibo.it, gigi{at}biocomp.unibo.it, piero{at}biocomp.unibo.it


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Brief Funct Genomic ProteomicHome page
R. Casadio, P. L. Martelli, and A. Pierleoni
The prediction of protein subcellular localization from sequence: a shortcut to functional genome annotation
Brief Funct Genomic Proteomic, February 18, 2008; (2008) eln003v1.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
M. T. A. Shamim, M. Anwaruddin, and H.A. Nagarajaram
Support Vector Machine-based classification of protein folds using the structural properties of amino acid residues and amino acid residue pairs
Bioinformatics, December 15, 2007; 23(24): 3320 - 3327.
[Abstract] [Full Text] [PDF]

Home page
 J Exp BotHome page
S. Schmidt von Braun, A. Sabetti, P. J. Hanic-Joyce, J. Gu, E. Schleiff, and P. B. M. Joyce
Dual targeting of the tRNA nucleotidyltransferase in plants: not just the signal
J. Exp. Bot., December 1, 2007; 58(15-16): 4083 - 4093.
[Abstract] [Full Text] [PDF]

Home page
 Protein Eng Des SelHome page
H.-B. Shen and K.-C. Chou
Nuc-PLoc: a new web-server for predicting protein subnuclear localization by fusing PseAA composition and PsePSSM
Protein Eng. Des. Sel., November 10, 2007; (2007) gzm057v1.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
A. Pierleoni, P. L. Martelli, P. Fariselli, and R. Casadio
eSLDB: eukaryotic subcellular localization database
Nucleic Acids Res., January 12, 2007; 35(suppl_1): D208 - D212.
[Abstract] [Full Text] [PDF]


Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.