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

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.
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Khalid Saeed; Władysław Homenda. 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2016, Vilnius, Lithuania. Springer International Publishing, Lecture Notes in Computer Science, LNCS-9842, pp.530-537, 2016, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-45378-1_47〉
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Katarzyna Stąpor, Piotr Fabian. Classification of Protein Interactions Based on Sparse Discriminant Analysis and Energetic Features. Khalid Saeed; Władysław Homenda. 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2016, Vilnius, Lithuania. Springer International Publishing, Lecture Notes in Computer Science, LNCS-9842, pp.530-537, 2016, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-45378-1_47〉. 〈hal-01637469〉

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