Hybrid Biogeography Based Simultaneous Feature Selection and Prediction of N-Myristoylation Substrate Proteins Using Support Vector Machines and Random Forest Classifiers

@inproceedings{Ghosh2012HybridBB,
  title={Hybrid Biogeography Based Simultaneous Feature Selection and Prediction of N-Myristoylation Substrate Proteins Using Support Vector Machines and Random Forest Classifiers},
  author={Shameek Ghosh and Nayana Ramachandran and C. Venkateshwari and Vaidyanathan K. Jayaraman},
  booktitle={SEMCCO},
  year={2012}
}
Majority of proteins undergo important post-translational modifications (PTM) that may alter physical and chemical properties of the protein and mainly their functions. Laboratory processes of determining PTM sites in proteins are laborious and expensive. On the contrary, computational approaches are far swifter and economical; and the models for prediction of PTMs can be quite accurate too. Among the PTMs, Protein N- terminal N-myristoylation by myristoyl-CoA protein N-myristoyltransferase… CONTINUE READING