Return to search

Cis-regulatory modules clustering from sequence similarity

I present a method that regroups cis-regulatory modules by shared sequences motifs. The goal of this approach is to search for clusters of modules that may share some function, using only sequence similarity. The proposed similarity measure is based on a variable-order Markov model likelihood scoring of sequences. I also introduce an extension of the variable-order Markov model which could better perform the required task. Results. I show that my method may recover subsets of sequences sharing a pattern in a set of generated sequences. I found that the proposed approach is successful in finding groups of modules that shared a type of transcription factor binding site.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.112632
Date January 2007
CreatorsHandfield, Louis-François.
PublisherMcGill University
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Formatapplication/pdf
CoverageMaster of Science (School of Computer Science.)
RightsAll items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated.
Relationalephsysno: 002712105, proquestno: AAIMR51278, Theses scanned by UMI/ProQuest.

Page generated in 0.0018 seconds