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Designing a feasible primer pair is an important work before performing polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) for single nucleotide polymorphism (SNP) genotyping. However, in many cases, no restriction enzymes are available to discriminate the target SNP, thus rendering the primer design useless. We propose a method that uses a genetic algorithm (GA) to search...
In this paper we proposed a novel genetic algorithm based on fuzzy system for identification CpG islands in human genome, called FGA-CGI (fuzzy GA-CpG Island). CpG islands play a fundamental role in genome analysis and annotation and contribute to increase the accuracy of promoter prediction. Recently, some approaches rely on large parameter space algorithms of predicting the CpG islands have been...
Many single nucleotide polymorphisms (SNPs) genotyping techniques have been developed but most of them are expensive. Polymerase chain reaction with confronting two-pair primers (PCR-CTPP) is a restriction enzyme-free and economic genotyping but its primer design is still computationally challenged. Here, we introduced a genetic algorithm (GA)-based PCR-CTPP primer design method. Thirty SNPs of the...
The feature selection process can be considered a problem of global combinatorial optimization in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in acceptable classification accuracy. In this study, we propose a combined filter method (ReliefF) and a wrapper method (memetic algorithm, MA) for classification. The goal of our method...
For microarray data classification problem, selecting relevant genes from microarray data pose a formidable challenge to researchers due to the high-dimensionality of features, multi-class categories being involved and the usually small sample size. In order to correctly analyze microarray data, the goal of feature (gene) selection is to select those subsets of differentially expressed genes that...
Gene expression profiles, which represent the state of a cell at a molecular level, have great potential as a medical diagnosis tool. Compared to the number of genes involved available training data sets generally have a fairly small sample size in cancer type classification. These training data limitations constitute a challenge to certain classification methodologies. The gene (feature) selection...
In order to provide feasible primer set for performing a polymerase chain reaction (PCR) experiment, many primer design methods have been proposed. However, the majority of these methods require a long time to obtain an optimal solution since quantities of template DNA need to be analyzed, and the designed primer sets usually do not provide a specific PCR product size. Evolutionary computation has...
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