Prediction of protein-protein interaction types using the decision templates

Wei Chen, Shao Wu Zhang, Yong Mei Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Protein-protein interactions (PPIs) play a key role in many cellular processes. Knowing about the multitude of PPIs can help the biological scientist understand the molecular mechanism of the cell. Unfortunately, it is both time-consuming and expensive to do so solely based on experiments. Therefore, developing computational approaches for predicting PPIs, PPI binding sites and PPI types would be of significant value. Here, we propose a novel method for predicting the PPI types based on decision templates. First, we introduce the concept of tensor product to construct three kinds of feature vectors which are the amino acid composition tensor product, the residue multi-scale conservation energy tensor product and the secondary structure content tensor product. Then, the correlation-based feature selection method was also used to reduce the dimensionality of these feature vectors. So, the protein pair can be represented by our three new kinds of feature vectors and Zhu's six kinds of feature vectors. The nine kinds of feature vectors are further taken as the inputs of individual support vector machine classifier respectively, and the outputs of these classifiers are aggregated with decision templates in decision level. The overall success rate obtained by jackknife cross-validation was 90.95%, indicating our method is very promising for predicting PPI types.

Original languageEnglish
Title of host publicationBIC-TA 2009 - Proceedings, 2009 4th International Conference on Bio-Inspired Computing
Subtitle of host publicationTheories and Applications
Pages93-98
Number of pages6
DOIs
StatePublished - 2009
Event2009 4th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2009 - Beijing, China
Duration: 16 Oct 200919 Oct 2009

Publication series

NameBIC-TA 2009 - Proceedings, 2009 4th International Conference on Bio-Inspired Computing: Theories and Applications

Conference

Conference2009 4th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2009
Country/TerritoryChina
CityBeijing
Period16/10/0919/10/09

Keywords

  • Correlation-based feature selection
  • Decision templates
  • Protein-protein interaction
  • Support vector machine
  • Tensor product

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