Abstract
Buhler and Tompa introduced the random projection algorithm for the motif discovery problem and demonstrated that this algorithm performs well on both simulated and biological samples. We describe a modification of the random projection algorithm, called the uniform projection algorithm, which utilizes a different choice of projections. We replace the random selection of projections by a greedy heuristic that approximately equalizes the coverage of the projections. We show that this change in selection of projections leads to improved performance on motif discovery problems. Furthermore, the uniform projection algorithm is directly applicable to other problems where the random projection algorithm has been used, including comparison of protein sequence databases.
Original language | English (US) |
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Pages (from-to) | 91-94 |
Number of pages | 4 |
Journal | IEEE/ACM Transactions on Computational Biology and Bioinformatics |
Volume | 1 |
Issue number | 2 |
DOIs | |
State | Published - Apr 2004 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Applied Mathematics
- Genetics
- Biotechnology
Keywords
- Combinatorial designs
- Low-discrepancy sequences
- Motif discovery
- Random projection
- Transcription factor binding sites