Name
Abstract | ||
|---|---|---|
Motif finding problems, abstracted as the planted (l, d)-motif finding problem, are a major task in molecular biology-finding functioning units and genes. In 2002, the random projection algorithm was introduced to solve the challenging (15, 4)-motif finding problem by using randomly chosen templates. Two years later, a so-called uniform projection algorithm was developed to improve the random projection algorithm by means of low-dispersion sequences generated by coverings. In this article, we introduce an improved projection algorithm called the low-dispersion projection algorithm, which uses low-dispersion sequences generated by developed almost difference families. Compared with the random projection algorithm, the low-dispersion projection algorithm can solve the (l, d)-motif finding problem with fewer templates without decreasing the success rate. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1089/cmb.2013.0054 | JOURNAL OF COMPUTATIONAL BIOLOGY |
Keywords | Field | DocType |
random projection,developed almost difference family,uniform projection,motif finding,low-dispersion sequence | Random projection,Combinatorics,Dykstra's projection algorithm,Algorithm,Artificial intelligence,DNA sequencing,Template,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
21.0 | 4 | 1066-5277 |
Citations | PageRank | References |
25 | 1.54 | 9 |
Authors | ||
3 | ||