CpGPAP: CpG island predictor analysis platform

CpGPAP is a web-based application that provides a user-friendly interface for predicting CpG islands in genome sequences or in user input sequences. The prediction algorithms supported in CpGPAP include complementary particle swarm optimization (CPSO), a complementary genetic algorithm (CGA) and other methods (CpGPlot, CpGProD and CpGIS) found in the literature. The CpGPAP platform is easy to use and has three main features (1) selection of the prediction algorithm; (2) graphic visualization of results; and (3) application of related tools and dataset downloads. These features allow the user to easily view CpG island results and download the relevant island data. CpGPAP is freely available at http://bio.kuas.edu.tw/CpGPAP/ webcite.The platform's supported algorithms (CPSO and CGA) provide a higher sensitivity and a higher correlation coefficient when compared to CpGPlot, CpGProD, CpGIS, and CpGcluster over an entire chromosome.CpG islands are stretches of typically unmethylated DNA with a high content of the two nucleic acids Cytosine (C) and Guanine (G), i.e., a high CG content relative to the bulk DNA. In typical mammalian genomes, many CpG islands (about 40%) are found in the promoter region. Of the estimated 45,000 CpG islands in the human genome, the overwhelming majority is found at the 5' end of genes. Identification and cloning of these CpG islands has proven very useful for finding and isolating genes. The CpG sites in the CpG islands of promoters are unmethylated if genes are expressed. It has thus been speculated that methylation of these sites plays a crucial role in gene expression [1].CpG islands were originally identified by Tykocinski and Max as small areas that contain the restriction enzyme HpaII in the genome and were thus called HpaII Tiny Fragment (HTF) islands [2]. Gardiner-Garden and Frommer (GGF) defined GpG islands as a DNA sequence with a length exceeding 200 bp, a GC content in that region of greater than 50%, and an Observed/Expected (O/E