Prediction of protein phosphorylation sites using classification trees and SVM classifier

Piotr Betkier , Zbigniew Szymański

Abstract

The paper presents a method of solving the problem of protein phosphorylation sites recognition. Six classifiers were created for prediction whether specified amino acid sequences represented as a 9-character strings react with given types of the kinase-enzymes. The method consists of three steps. Positions in the amino acid sequences significant for classification are found with the use of classification trees in the first step. Afterwards, the symbols composing the sequences are mapped to the real numbers domain using the Gini index method. The last step consists of creating the SVM classifiers as the final prediction models. The paper contains evaluation of the obtained results and the description of the methods applied to evaluate the quality of the classifiers.
Author Piotr Betkier II
Piotr Betkier,,
- The Institute of Computer Science
, Zbigniew Szymański II
Zbigniew Szymański,,
- The Institute of Computer Science
Pages1-8
Book Romaniuk Ryszard (eds.): Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2011 (Proceedings Volume), vol. 8008, 2011, SPIE, ISBN 9780819485823, 614 pages; 71 papers; N/A
DOIDOI:10.1117/12.905778
Languageen angielski
Score (nominal)10
Citation count*2 (2018-06-18)
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