Name
Abstract | ||
|---|---|---|
We address the problem of detecting consensus motifs, that occur with subtle variations, across multiple sequences. These are usually functional domains in DNA sequences such as transcriptional binding factors or other regulatory sites. The problem in its generality has been considered difficult and various benchmark data serve as the litmus test for different computational methods. We present a method centered around unsupervised combinatorial pattern discovery. The parameters are chosen using a careful statistical analysis of consensus motifs. This method works well on the benchmark data and is general enough to be extended to a scenario where the variation in the consensus motif includes indels (along with mutations). We also present some results on detection of transcription binding factors in human DNA sequences. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.tcs.2008.01.017 | Theor. Comput. Sci. |
Keywords | DocType | Volume |
Pattern discovery,litmus test,subtle variation,different computational method,human DNA sequence,consensus motif,transcriptional binding factor,benchmark data,functional domain,careful statistical analysis,various benchmark data,transcription binding factor,Consensus motifs,Transcription factors,Binding sites,Subtle motifs | Journal | 395 |
Issue | ISSN | Citations |
2-3 | Theoretical Computer Science | 7 |
PageRank | References | Authors |
0.46 | 14 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matteo Comin | 1 | 191 | 20.94 |
| Laxmi Parida | 2 | 773 | 77.21 |