Using search engine technology for protein function prediction

  • Authors:

  • Ziyang Chen;Zhao Cai;Min Li;Binbin Liu

  • Affiliations:

  • College of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China.;School of Information Science and Engineering, Central South University, Changsha 410083, China.;School of Information Science and Engineering, Central South University, Changsha 410083, China.;School of Information Science and Engineering, Central South University, Changsha 410083, China

  • Venue:
  • International Journal of Bioinformatics Research and Applications
  • Year:
  • 2011

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Abstract

Prediction of protein function is one of the most challenging problems in the post-genomic era. In this paper, we propose a novel algorithm Improved ProteinRank (IPR) for protein function prediction, which is based on the search engine technology and the preferential attachment criteria. In addition, an improved algorithm IPRW is developed from IPR to be used in the weighted protein protein interaction (PPI) network. The proposed algorithms IPR and IPRW are applied to the PPI network of S.cerevisiae. The experimental results show that both IPR and IPRW outweigh the previous methods for the prediction of protein functions.