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Classification of Protein Interactions Based on Sparse Discriminant Analysis and Energetic Features

  • Katarzyna Stąpor
  • Piotr FabianEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9842)

Abstract

Prediction of protein-protein interaction (PPI) types is an important problem in life sciences because of fundamental role of PPIs in many biological processes. In this paper we propose a new classification approach based on the extended classical Fisher linear discriminant analysis (FLDA) to predict obligate and non-obligate protein-protein interactions. To characterize properties of the protein interaction, we proposed to use the binding free energies (total of 282 features). The obtained results are better than in the previous studies.

Keywords

Sparse discriminant analysis Feature selection Protein-protein interaction 

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© IFIP International Federation for Information Processing 2016

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Authors and Affiliations

  1. 1.Faculty of Automatic Control, Electronics and Computer ScienceSilesian Technical UniversityGliwicePoland

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