Name
Abstract | ||
|---|---|---|
Researchers should select a suitable subgroup that includes all SNPs and represents the rest of the SNPs with little error for very large-scale association studies. The SNPs included in the subgroup are tag SNPs or haplotype tag SNPs (htSNPs). When selecting the tag SNPs, it is critical to accurately predict and identify the smallest number of tag SNPs with minimum error. This study used the Clonal Selection Algorithm (CLONALG) to decide on the tag SNPs to be included in the subgroup. In addition, the study proposed a new method called CSMV, which used the Majority Voting (MV) method to predict the rest of the SNPs. This method was compared with the BPSO method and the CLONTagger with parameter optimisation method using datasets of different sizes. According to the experimental results of the study, the CSMV method could determine the tag SNPs with significantly higher accuracy than the other two methods. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1504/IJDMB.2016.10003176 | INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS |
Keywords | Field | DocType |
ABC, artificial bee colony algorithm, CLONALG, clonal selection algorithm, majority voting, SVM, support vector machine, tag SNPs | Computer science,Tag SNP,Support vector machine,Haplotype,Genetic association,Single-nucleotide polymorphism,Bioinformatics,Clonal selection algorithm,Majority rule,Clonal selection | Journal |
Volume | Issue | ISSN |
16 | 4 | 1748-5673 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ilhan Ilhan | 1 | 12 | 1.90 |
| Gülay Tezel | 2 | 104 | 7.40 |