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BioMed Research International
Volume 2014, Article ID 282343, 10 pages
Research Article

WISCOD: A Statistical Web-Enabled Tool for the Identification of Significant Protein Coding Regions

1Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestraße 63–73, 14195 Berlin, Germany
2Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, 04103 Leipzig, Germany
3Department of Statistics, University of Barcelona, Avenida Diagonal 643, 08028 Barcelona, Spain

Received 1 May 2013; Revised 18 December 2013; Accepted 11 February 2014; Published 15 September 2014

Academic Editor: Vladimir Bajic

Copyright © 2014 Mireia Vilardell et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Classically, gene prediction programs are based on detecting signals such as boundary sites (splice sites, starts, and stops) and coding regions in the DNA sequence in order to build potential exons and join them into a gene structure. Although nowadays it is possible to improve their performance with additional information from related species or/and cDNA databases, further improvement at any step could help to obtain better predictions. Here, we present WISCOD, a web-enabled tool for the identification of significant protein coding regions, a novel software tool that tackles the exon prediction problem in eukaryotic genomes. WISCOD has the capacity to detect real exons from large lists of potential exons, and it provides an easy way to use global value called expected probability of being a false exon (EPFE) that is useful for ranking potential exons in a probabilistic framework, without additional computational costs. The advantage of our approach is that it significantly increases the specificity and sensitivity (both between 80% and 90%) in comparison to other ab initio methods (where they are in the range of 70–75%). WISCOD is written in JAVA and R and is available to download and to run in a local mode on Linux and Windows platforms.