Mining the Arabidopsis thaliana genome for highly-divergent seven transmembrane receptors

Authors

Etsuko N. Moriyama, University of Nebraska-LincolnFollow
Pooja K. Strope, University of Nebraska-Lincoln
Stephen O. Opiyo, University of Nebraska-Lincoln
Zhongying Chen, University of North Carolina
Alan M. Jones, University of North Carolina at Chapel HillFollow

Document Type

Article

Date of this Version

10-25-2006

Citation

Genome Biology 2006, 7:R96 (doi:10.1186/gb-2006-7-10-r96).

Comments

© 2006 Moriyama et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License. Used by permission.

Abstract

To identify divergent seven-transmembrane receptor (7TMR) candidates from the Arabidopsis thaliana genome, multiple protein classification methods were combined, including both alignmentbased and alignment-free classifiers. This resolved problems in optimally training individual classifiers using limited and divergent samples, and increased stringency for candidate proteins. We identified 394 proteins as 7TMR candidates and highlighted 54 with corresponding expression patterns for further investigation.