Name
Abstract | ||
|---|---|---|
This paper describes a new strategy for designing degenerate primers for a given multiple alignment of amino acid sequences. Degenerate primers are useful for amplifying homologous genes. However, when a large collection of sequences is considered, no consensus region may exist in the multiple alignment, making it impossible to design a single pair of primers for the collection. In such cases, manual methods are used to find smaller groups from the input collection so that primers can be designed for individual groups. Our strategy proposes an automatic grouping of the input sequences by using clustering techniques. Conserved regions are then detected for each individual group. Conserved regions are scored using a BlockSimilarity score, a novel alignment scoring scheme that is appropriate for this application. Degenerate primers are then designed by reverse translating the conserved amino acid sequences to the corresponding nucleotide sequences. Our program, DePiCt, was written in BioPerl and was tested on the Toll-Interleukin Receptor (TIR)and the non-TIR family of plant resistance genes. Existing programs for degenerate primer design were unable to find primers for these data sets. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/CSB.2003.1227306 | CSB |
Keywords | Field | DocType |
individual group,blocksimilarity score,input collection,conserved regionsare,degenerate primer design,conserved amino acid sequencesto,automatic grouping,multiple alignment ofamino acid,degenerateprimer design,multiple alignment,conserved region,amino acid sequence,proteins,genetics,nucleotide sequence,statistical analysis,sequences | Degenerate energy levels,Cellular biophysics,Gene,Computer science,Primer (molecular biology),Bioinformatics,Multiple sequence alignment,Cluster analysis,Statistical analysis | Conference |
Volume | ISSN | ISBN |
2 | 1555-3930 | 0-7695-2000-6 |
Citations | PageRank | References |
4 | 0.52 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xintao Wei | 1 | 7 | 1.29 |
| David N Kuhn | 2 | 10 | 1.01 |
| Giri Narasimhan | 3 | 814 | 77.96 |