PhyloGibbs: A Gibbs Sampler Incorporating Phylogenetic Information View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2005

AUTHORS

Rahul Siddharthan , Erik van Nimwegen , Eric D. Siggia

ABSTRACT

We present a new Gibbs sampler algorithm with the motivation of finding motifs, representing candidate binding sites for transcription factors, in closely related species. Since much conservation here arises not from the existence of functional sites but simply from the lack of sufficient evolutionary divergence between the species, a conventional Gibbs sampler will fail. We compare the effectiveness against conventional methods on closely-related yeast sequences. Our algorithm is also applicable to single-species or phylogenetically-unrelated sequences, and has further improvements over previous Gibbs samplers, including accounting for correlations in the “background” model, an option to search for “dimers” (pairs of motifs with variable spacing), and a “tracking” strategy that allows us to assess the significance of candidate motifs. More... »

PAGES

30-41

Book

TITLE

Regulatory Genomics

ISBN

978-3-540-24456-1
978-3-540-32280-1

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-32280-1_4

DOI

http://dx.doi.org/10.1007/978-3-540-32280-1_4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1023472380


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