Mining the Arabidopsis thaliana genome for highly-divergent seven transmembrane receptors
Mining the Arabidopsis thaliana genome for highly-divergent seven transmembrane receptors
AbstractTo 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.
- University of North Carolina at Greensboro United States
- University of North Carolina at Chapel Hill United States
- University of Nebraska-Lincoln United States
- University of North Carolina System United States
- UNIVERSITY OF NEBRASKA United States
570, Arabidopsis Proteins, Gene Expression Profiling, Genetic Vectors, Arabidopsis, Life Sciences, Method, Genetic Variation, Receptors, Cell Surface, Markov Chains, Databases, Protein, Biology, Genome, Plant
570, Arabidopsis Proteins, Gene Expression Profiling, Genetic Vectors, Arabidopsis, Life Sciences, Method, Genetic Variation, Receptors, Cell Surface, Markov Chains, Databases, Protein, Biology, Genome, Plant
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