{"title":"A Gibbs sampling algorithm for motif discovery using a linear mixed model","authors":"Daming Lu","doi":"10.1145/1722024.1722053","DOIUrl":null,"url":null,"abstract":"The identification of motifs in the gene promoters is a critical step in the delineation of the genetic regulatory framework of an organism. In this paper, a new linear mixed model is introduced. This model is a combination of the conventional Position Weight Matrix (PWM) model and a novel Mutual Information (MI) model. PWM can contain individual position frequencies whereas MI can reflect pair wise relation between positions. A training stage is carried out to determine the weight of each model. After that this trained model is embedded into a Gibbs sampling algorithm for motif discovery. After analyzing a set of DNA sequences using this program, putative motifs are gained and compared with experimental verified motifs as well as other popular motif finding software. Results show that this new mixed model can improve motif discovery accuracy to some extent.","PeriodicalId":39379,"journal":{"name":"In Silico Biology","volume":"1 1","pages":"25"},"PeriodicalIF":0.0000,"publicationDate":"2010-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/1722024.1722053","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"In Silico Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1722024.1722053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 1
Abstract
The identification of motifs in the gene promoters is a critical step in the delineation of the genetic regulatory framework of an organism. In this paper, a new linear mixed model is introduced. This model is a combination of the conventional Position Weight Matrix (PWM) model and a novel Mutual Information (MI) model. PWM can contain individual position frequencies whereas MI can reflect pair wise relation between positions. A training stage is carried out to determine the weight of each model. After that this trained model is embedded into a Gibbs sampling algorithm for motif discovery. After analyzing a set of DNA sequences using this program, putative motifs are gained and compared with experimental verified motifs as well as other popular motif finding software. Results show that this new mixed model can improve motif discovery accuracy to some extent.
In Silico BiologyComputer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍：
The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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