Randomized algorithms for motif detection

Motif detection for DNA sequences has many important applications in biological studies, e.g. locating binding sites regulatory signals, designing genetic probes etc. In this paper, we propose a randomized algorithm, design an improved EM algorithm and combine them to form a software tool. (1) We de...

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Vydáno v:Journal of bioinformatics and computational biology Ročník 3; číslo 5; s. 1039
Hlavní autoři: Wang, Lusheng, Dong, Liang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Singapore 01.10.2005
Témata:
Algorithms
Conserved Sequence
Data Interpretation, Statistical
DNA - chemistry
DNA - genetics
Likelihood Functions
Models, Genetic
Models, Statistical
Sequence Alignment - methods
Sequence Analysis, DNA - methods
Sequence Homology, Nucleic Acid
ISSN:0219-7200
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Shrnutí:Motif detection for DNA sequences has many important applications in biological studies, e.g. locating binding sites regulatory signals, designing genetic probes etc. In this paper, we propose a randomized algorithm, design an improved EM algorithm and combine them to form a software tool. (1) We design a randomized algorithm for consensus pattern problem. We can show that with high probability, our randomized algorithm finds a pattern in polynomial time with cost error at most x l for each string, where l is the length of the motif and can be any positive number given by the user. (2) We design an improved EM algorithm that outperforms the original EM algorithm. (3) We develop a software tool, MotifDetector, that uses our randomized algorithm to find good seeds and uses the improved EM algorithm to do local search. We compare MotifDetector with Buhler and Tompa's PROJECTION which is considered to be the best known software for motif detection. Simulations show that MotifDetector is slower than PROJECTION when the pattern length is relatively small, and outperforms PROJECTION when the pattern length becomes large. It is available for free at http://www.cs.cityu.edu.hk/~lwang/software/motif/index.html, subject to copyright restrictions.
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ISSN:0219-7200
DOI:10.1142/s0219720005001508