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WISCOD: A Statistical Web-Enabled Tool for the Identification of Significant Protein Coding Regions
Joint Authors
Vilardell, Mireia
Parra, Genis
Civit, Sergi
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-09-15
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
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 P 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.
American Psychological Association (APA)
Vilardell, Mireia& Parra, Genis& Civit, Sergi. 2014. WISCOD: A Statistical Web-Enabled Tool for the Identification of Significant Protein Coding Regions. BioMed Research International،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1016197
Modern Language Association (MLA)
Vilardell, Mireia…[et al.]. WISCOD: A Statistical Web-Enabled Tool for the Identification of Significant Protein Coding Regions. BioMed Research International No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1016197
American Medical Association (AMA)
Vilardell, Mireia& Parra, Genis& Civit, Sergi. WISCOD: A Statistical Web-Enabled Tool for the Identification of Significant Protein Coding Regions. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1016197
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1016197