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A New Machine Learning Approach for Protein Phosphorylation Site Prediction in Plants

  • Jianjiong Gao
  • Ganesh Kumar Agrawal
  • Jay J. Thelen
  • Zoran Obradovic
  • A. Keith Dunker
  • Dong Xu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5462)

Abstract

Protein phosphorylation is a crucial regulatory mechanism in various organisms. With recent improvements in mass spectrometry, phosphorylation site data are rapidly accumulating. Despite this wealth of data, computational prediction of phosphorylation sites remains a challenging task. This is particularly true in plants, due to the limited information on substrate specificities of protein kinases in plants and the fact that current phosphorylation prediction tools are trained with kinase-specific phosphorylation data from non-plant organisms. In this paper, we proposed a new machine learning approach for phosphorylation site prediction. We incorporate protein sequence information and protein disordered regions, and integrate machine learning techniques of k-nearest neighbor and support vector machine for predicting phosphorylation sites. Test results on the PhosPhAt dataset of phosphoserines in Arabidopsis and the TAIR7 non-redundant protein database show good performance of our proposed phosphorylation site prediction method.

Keywords

Protein Phosphorylation Phosphoproteomics Arabidopsis Protein Disorder KNN SVM 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jianjiong Gao
    • 1
    • 2
  • Ganesh Kumar Agrawal
    • 2
    • 3
  • Jay J. Thelen
    • 2
    • 3
  • Zoran Obradovic
    • 4
  • A. Keith Dunker
    • 5
  • Dong Xu
    • 1
    • 2
  1. 1.Department of Computer ScienceUSA
  2. 2.C.S. Bond Life Sciences CenterUSA
  3. 3.Department of BiochemistryUniversity of MissouriColumbiaUSA
  4. 4.Center for Information Science and TechnologyTemple UniversityPhiladelphiaUSA
  5. 5.Center for Computational Biology and BioinformaticsIndiana University Schools of Medicine and InformaticsIndianapolisUSA

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