Using Inductive Logic Programming for Predicting Protein-Protein Interactions from Multiple Genomic Data

Protein-protein interactions play an important role in many fundamental biological processes. Computational approaches for predicting protein-protein interactions are essential to infer the functions of unknown proteins, and to validate the results obtained of experimental methods on protein-protein...

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Hauptverfasser: Tran, Tuan Nam, Satou, Kenji, Ho, Tu Bao
Format: Buchkapitel
Sprache:eng
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Zusammenfassung:Protein-protein interactions play an important role in many fundamental biological processes. Computational approaches for predicting protein-protein interactions are essential to infer the functions of unknown proteins, and to validate the results obtained of experimental methods on protein-protein interactions. We have developed an approach using Inductive Logic Programming (ILP) for protein-protein interaction prediction by exploiting multiple genomic data including protein-protein interaction data, SWISS-PROT database, cell cycle expression data, Gene Ontology, and InterPro database. The proposed approach demonstrates a promising result in terms of obtaining high sensitivity/specificity and comprehensible rules that are useful for predicting novel protein-protein interactions. We have also applied our method to a number of protein-protein interaction data, demonstrating an improvement on the expression profile reliability (EPR) index.
ISSN:0302-9743
1611-3349
DOI:10.1007/11564126_33