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A Statistical Web-Enabled Tool for the Identification of Significant Protein Coding Regions. 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-values 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 initiomethods (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. (BioMed Research International Volume 2014, Article ID 282343, 10 pages).