Mining the Arabidopsis and rice genomes for cyclophilin protein families

  • Authors:

  • S. O. Opiyo;E. N. Moriyama

  • Affiliations:

  • Department of Agronomy and Horticulture, University of Nebraska-Lincoln 68583, USA.;School of Biological Sciences and Center for Plant Science Innovation, University of Nebraska-Lincoln, 403 Manter Hall, Lincoln, NE 68588-0118, USA

  • Venue:
  • International Journal of Bioinformatics Research and Applications
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Cyclophilins, which possess peptidyl-prolyl isomerase activity, are cellular targets of immunosuppressant drugs and involved in a wide variety of functions. While the Arabidopsis thaliana genome contains the largest number of cyclophilins, the number of plant cyclophilins available in databases is small compared to that of other organisms. It implies that many cyclophilins are yet to be identified in plants. In order to identify cyclophilin candidates from available plant sequence data, we examined alignment-free methods based on Partial Least Squares (PLS). PLS classifier performed better than profile hidden Markov models and PSI-BLAST in identifying cyclophilins from the Arabidopsis and rice genomes.