Using Phylogenetic Relationships to Improve the Inference of Transcriptional Regulatory Networks

Détails

ID Serval
serval:BIB_92F4FC5F163D
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Titre
Using Phylogenetic Relationships to Improve the Inference of Transcriptional Regulatory Networks
Titre de la conférence
BMEI 2008, International Conference on BioMedical Engineering and Informatics
Auteur⸱e⸱s
Zhang X., Zaheri M., Moret B.M.E.
Adresse
Sanya, Hainan , China, May 27-30, 2008
Statut éditorial
Publié
Date de publication
2008
Volume
1
Pages
186-193
Langue
anglais
Résumé
Inferring transcriptional regulatory networks from gene- expression data remains a challenging problem, in part because of the noisy nature of the data and the lack of strong network models. Time-series expression data have shown promise and recent work by Babu on the evolution of regulatory networks in E. coli and S. cerevisiae opened another avenue of investigation. In this paper we take the evolutionary approach one step further. We conjecture that established phylogenetic relationships among a group of related organisms can be used to improve the inference of regulatory networks for these organisms from expression data gathered under similar conditions. We develop an inference algorithm to take advantage of such information and present the results of simulations (including various tests to exclude confounding factors) that clearly show the added value of the phylogenetic information. Our algorithm and results offer support for our conjecture and indicate that gene-expression studies under identical conditions across a range of related organisms could yield significantly more accurate regulatory networks than single-organism studies.
Création de la notice
29/07/2008 10:22
Dernière modification de la notice
20/08/2019 14:55
Données d'usage