G protein-coupled receptor classification at the subfamily level with probabilistic suffix tree

Jingyi Yang, Jitender Deogun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Classifying G protein-coupled receptors (GPCRs) is an interesting topic because of the important role of GPCRs in pharmaceutical research. GPCRs have diverse functions and are involved in many biological processes, which makes them an ideal target of novel medicine. The diverse nature of GPCRs results in the lack of overall sequence homolog among the members, making the classification of GPCRs a very challenging task. Various approaches and methods have been applied to this task, such as HMM, decision tree, and SVM. However, their performances are not completely satisfactory. In this paper, we propose a new method to classify GPCRs into different subfamilies. In the proposed method, the probabilistic suffix tree (PST) is used to construct a prediction model for each of the subfamilies. To classify a GPCR protein, we calculate its similarity score against the PST prediction model of each subfamily using the multi-domain local prediction algorithm. The protein is then classified into the subfamily which gives it the highest score. Our method only uses the primary sequence information and is also very efficient. The model construction and prediction process takes very short time. However, it reports the 98.07% and 97.35% overall accuracy on the level I and II subfamily classification in a 2-fold cross validation test respectively. Given the high accuracy and efficiency, our method is a significant improvement on previously reported ones.

Original languageEnglish (US)
Title of host publicationProceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06
Pages490-497
Number of pages8
DOIs
StatePublished - Dec 1 2006
Event3rd Computational Intelligence in Bioinformatics and Computational Biology Symposium, CIBCB - Toronto, ON, Canada
Duration: Sep 28 2006Sep 29 2006

Publication series

NameProceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06

Conference

Conference3rd Computational Intelligence in Bioinformatics and Computational Biology Symposium, CIBCB
CountryCanada
CityToronto, ON
Period9/28/069/29/06

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Keywords

  • GPCR protein classification
  • Multi-domain local prediction
  • Probabilistic suffix tree

ASJC Scopus subject areas

  • Artificial Intelligence
  • Biomedical Engineering
  • Applied Mathematics
  • Computational Mathematics

Cite this

Yang, J., & Deogun, J. (2006). G protein-coupled receptor classification at the subfamily level with probabilistic suffix tree. In Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06 (pp. 490-497). [4133212] (Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06). https://doi.org/10.1109/CIBCB.2006.330976