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Regions with abundant GC nucleotides in a genome, which are often referred to as CpG islands, have been used in methylation analysis and the prediction of promoter regions. In this study, we propose PSOEO (Particle Swarm Optimization with Extremal Optimization), a method for the prediction of CpG islands in the mammal genome. This method adopts the GGF criteria (GC content ¡Ù 50%, observed/expected...
In the current researches of disease-gene association, Single Nucleotide Polymorphism (SNP) is the most interested topic. However, genotyping all existing SNPs for a large number of samples is still challenging even though SNP arrays have been developed to facilitate the task. Therefore, it is essential to select only informative SNPs (tag SNP) representing the rest SNPs for genome-wide association...
Single nucleotide polymorphisms (SNPs) hold much promise as a basis for disease-gene association. However, they are limited by the cost of genotyping the tremendous number of SNPs. It is therefore essential to select only informative subsets (tag SNPs) out of all SNPs. Several promising methods for tag SNP selection have been proposed, such as the haplotype block-based and block-free approaches. The...
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