%0 Conference Proceedings
%T Classification of Protein Interactions Based on Sparse Discriminant Analysis and Energetic Features
%+ Silesian Technical University
%A Stąpor, Katarzyna
%A Fabian, Piotr
%Z Part 7: Decisions
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM)
%C Vilnius, Lithuania
%Y Khalid Saeed
%Y Władysław Homenda
%I Springer International Publishing
%3 Computer Information Systems and Industrial Management
%V LNCS-9842
%P 530-537
%8 2016-09-14
%D 2016
%R 10.1007/978-3-319-45378-1_47
%K Sparse discriminant analysis
%K Feature selection
%K Protein-protein interaction
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X 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.
%G English
%Z TC 8
%2 https://inria.hal.science/hal-01637469/document
%2 https://inria.hal.science/hal-01637469/file/419526_1_En_47_Chapter.pdf
%L hal-01637469
%U https://inria.hal.science/hal-01637469
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC8
%~ IFIP-CISIM
%~ IFIP-LNCS-9842