A probabilistic method to detect regulatory modules

Sinha, Saurabh and van Nimwegen, Erik and Siggia, Eric D.. (2003) A probabilistic method to detect regulatory modules. Bioinformatics, 19 (Supplement 1). i292-i301.

Full text not available from this repository.

Official URL: https://edoc.unibas.ch/83039/

Downloads: Statistics Overview


The discovery of cis-regulatory modules in metazoan genomes is crucial for understanding the connection between genes and organism diversity.; We develop a computational method that uses Hidden Markov Models and an Expectation Maximization algorithm to detect such modules, given the weight matrices of a set of transcription factors known to work together. Two novel features of our probabilistic model are: (i) correlations between binding sites, known to be required for module activity, are exploited, and (ii) phylogenetic comparisons among sequences from multiple species are made to highlight a regulatory module. The novel features are shown to improve detection of modules, in experiments on synthetic as well as biological data.
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Bioinformatics (van Nimwegen)
UniBasel Contributors:van Nimwegen, Erik
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Oxford University Press
Note:Publication type according to Uni Basel Research Database: Journal article
Identification Number:
Last Modified:18 May 2021 10:01
Deposited On:18 May 2021 10:01

Repository Staff Only: item control page