Combining Phylogenetic Profiling-Based and Machine Learning-Based Techniques to Predict Functional Related Proteins

Tzu Wen Lin, Jian Wei Wu, Darby Tien Hao Chang

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Annotating protein functions and linking proteins with similar functions are important in systems biology. The rapid growth rate of newly sequenced genomes calls for the development of computational methods to help experimental techniques. Phylogenetic profiling (PP) is a method that exploits the evolutionary co-occurrence pattern to identify functional related proteins. However, PP-based methods delivered satisfactory performance only on prokaryotes but not on eukaryotes. This study proposed a two-stage framework to predict protein functional linkages, which successfully enhances a PP-based method with machine learning. The experimental results show that the proposed two-stage framework achieved the best overall performance in comparison with three PP-based methods.

Original languageEnglish
Article numbere75940
JournalPloS one
Volume8
Issue number9
DOIs
Publication statusPublished - 2013 Sep 19

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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