Name
Abstract | ||
|---|---|---|
Simple sequence repeats (SSRs) play as important genetic markers in genome mapping projects and polymorphic research. In this study, we have designed a database which facilitates the searching and position verification of SSRs and provides comparative genomics information among various species. However, performing in silico analysis of biological data sometimes attempts to result in high false positive rates. In order to promote the specificity of discovered SSRs from the proposed system, we take advantage of evolutionarily conserved segments among sequences from various species. Users are able to choose specific species as targets to filter out SSRs which are not located in conserved regions. Screening processes narrow down candidate SSRs and improve the performance of specificity. In this database, there are eleven representative species collected for comparative genomics analysis. Taking the comparison between zebrafish and medaka fish as an example, 60,363 SSRs from zebrafish genome are found in conserved regions in which 6.20% SSRs are located in protein-coding regions, 0.20% in 5psilaUTR, 0.87% in 3psilaUTR, 51.26% in intron, and 41.45% in intergenic region. Each SSR is precisely allocated and annotated in this database for further applications. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/CISIS.2008.148 | CISIS |
Keywords | Field | DocType |
simple sequence repeat,database,database management systems,genome mapping projects,screening processes,ssr comparative genomics database,genetic markers,position verification,silico analysis,genetics,eleven representative species,specific species,biology computing,candidate ssrs,evolutionarily conserved segment,polymorphic research,simple sequence repeats,comparative genomics analysis,comparative genomics,comparative genomics information,genome mapping project,various species,conserved region,genome mapping,genetic marker,dna,proteins,genomics,sequences,bioinformatics,biological data,biology,false positive rate,databases,polymorphism,gene expression | Genome,Biological data,Microsatellite,Computer science,Gene mapping,Comparative genomics,Genomics,Intergenic region,Database,In silico | Conference |
ISBN | Citations | PageRank |
978-0-7695-3109-0 | 0 | 0.34 |
References | Authors | |
1 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tun-Wen Pai | 1 | 127 | 29.71 |
| Meng-Chang Hsiao | 2 | 0 | 0.34 |
| Chien-Ming Chen | 3 | 0 | 2.37 |
| Wen-Shyong Tzou | 4 | 43 | 5.99 |
| Ron-Shan Chen | 5 | 0 | 1.01 |