### Abstract

Motivation: The problem of finding transcription factor binding sites in the upstream regions of given genes is algorithmically an interesting and challenging problem in computational biology. A degenerate pattern over a finite alphabet ∑ is a sequence of subsets of ∑. A string over IUPAC nucleic acid codes is also a degenerate pattern over ∑ = {A, C, G, T}, and is used as one of the major patterns modeling transcription factor binding sites in the upstream regions of genes. However, it is known that the problem of finding a degenerate pattern consistent with both positive and negative string sets is in general NP-complete. Our aim is to devise a heuristic algorithm to find a degenerate pattern which is optimal for positive and negative string sets w.r.t. a given score function. Results: We have proposed an enumerative algorithm called SUPERPOSITION for finding optimal degenerate patterns with a pruning technique, which works with most all reasonable score functions. The performance score of the algorithm has been compared with those of other popular motif-finding algorithms YMF, MEME and AlignACE on various sets of co-regulated genes of yeast. In the computational experiment, SUPERPOSITION has outperformed the others on several gene sets. Availability: The python script SUPERPOSITION is available at http://www.math.kyushu-u.ac.jp/~om/softwares.html.

Original language | English |
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Pages (from-to) | ii206-ii214 |

Journal | Bioinformatics |

Volume | 19 |

Issue number | SUPPL. 2 |

DOIs | |

Publication status | Published - Dec 1 2003 |

### All Science Journal Classification (ASJC) codes

- Statistics and Probability
- Biochemistry
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Computational Mathematics

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## Cite this

*Bioinformatics*,

*19*(SUPPL. 2), ii206-ii214. https://doi.org/10.1093/bioinformatics/btg1079