Prediction of midbody, centrosome and kinetochore proteins based on gene ontology information

Biochem Biophys Res Commun. 2010 Oct 22;401(3):382-4. doi: 10.1016/j.bbrc.2010.09.061. Epub 2010 Sep 18.

Abstract

In the process of cell division, a great deal of proteins is assembled into three distinct organelles, namely midbody, centrosome and kinetochore. Knowing the localization of microkit (midbody, centrosome and kinetochore) proteins will facilitate drug target discovery and provide novel insights into understanding their functions. In this study, a support vector machine (SVM) model, MicekiPred, was presented to predict the localization of microkit proteins based on gene ontology (GO) information. A total accuracy of 77.51% was achieved using the jackknife cross-validation. This result shows that the model will be an effective complementary tool for future experimental study. The prediction model and dataset used in this article can be freely downloaded from http://cobi.uestc.edu.cn/people/hlin/tools/MicekiPred/.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artificial Intelligence*
  • Cell Cycle Proteins / chemistry
  • Cell Cycle Proteins / genetics
  • Cell Cycle Proteins / metabolism*
  • Cell Division / genetics*
  • Centrosome*
  • Kinetochores
  • Sequence Analysis, Protein / methods*

Substances

  • Cell Cycle Proteins