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

Etsuko N Moriyama¹ , Pooja K Strope¹ , Stephen O Opiyo² , Zhongying Chen³ and Alan M Jones³

¹School of Biological Sciences and Plant Science Initiative, University of Nebraska-Lincoln, Lincoln, NE 68588-0660, USA

²Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583-0915, USA

³Departments of Biology and Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA

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Genome Biology 2006, 7:R96doi:10.1186/gb-2006-7-10-r96


Published:	25 October 2006

Subject areas: Bioinformatics, Plant biology

Abstract

To identify divergent seven-transmembrane receptor (7TMR) candidates from the Arabidopsis thaliana genome, multiple protein classification methods were combined, including both alignment-based 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.