An Improved Gibbs Sampling Algorithm for Finding TFBS

Computational methods detecting the transcription factor binding sites (TFBS) remain one of the most intriguing and challenging subjects in bioinformatics. Gibbs sampling is essentially a heuristic method, and it is easy to trap into a nonoptimal “local maximum”. To overcome this problem and to impr...

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Bibliographic Details
Published inComputational Intelligence and Security pp. 927 - 932
Main Authors He, Caisheng, Dai, Xianhua
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
SeriesLecture Notes in Computer Science
Subjects
Background Model
Gibbs Sampling Algorithm
Motif Finding
Position Weight Matrix
Transcription Factor Binding Site
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ISBN9783540308188
3540308180
ISSN0302-9743
1611-3349
DOI10.1007/11596448_138

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Summary:Computational methods detecting the transcription factor binding sites (TFBS) remain one of the most intriguing and challenging subjects in bioinformatics. Gibbs sampling is essentially a heuristic method, and it is easy to trap into a nonoptimal “local maximum”. To overcome this problem and to improve the accuracy and sensitivity of the algorithm, we present an improved Gibbs sampling strategy MPWMGMS to search for TFBS. We have tested MPWMGMS and other existing Gibbs sampling algorithms on simulated data and real biological data sets with regulatory elements. The results indicate that MPWMGMS has better performance than other methods to a great extent in accuracy and sensitivity of finding true TFBS.
Bibliography:This work is supported by National Science Foundation grant 60474075 of China.
ISBN:9783540308188
3540308180
ISSN:0302-9743
1611-3349
DOI:10.1007/11596448_138