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Incorporating multiple genomic features with the utilization of interacting domain patterns to improve the prediction of protein-protein interactions

Roslan, Rosfuzah and Othman, Muhamad Razib and Ali Shah, Zuraini and Kasim, Shahreen and Asmuni, Hishammuddin and Taliba, Jumail and Hassan, Rohayanti and Zakaria, Zalmiyah (2010) Incorporating multiple genomic features with the utilization of interacting domain patterns to improve the prediction of protein-protein interactions. Information Sciences, 180 (20). pp. 3955-3973. ISSN 0020-0255

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Official URL: http://dx.doi.org/10.1016/j.ins.2010.06.041

Abstract

Protein-protein interaction (PPI) networks play an outstanding role in the organization of life. Parallel to the growth of experimental techniques on determining PPIs, the emergence of computational methods has greatly accelerated the time needed for the identification of PPIs on a wide genomic scale. Although experimental approaches have limitations that can be complemented by the computational methods, the results from computational methods still suffer from high false positive rates which contribute to the lack of solid PPI information. Our study introduces the PPI-Filter; a computational framework aimed at improving PPI prediction results. It is a post-prediction process which involves filtration, using information based on three different genomic features; (i) gene ontology annotation (GOA), (ii) homologous interactions and (iii) protein families (PFAM) domain interactions. In the study, we incorporated a protein function prediction method, based on interacting domain patterns, the protein function predictor or PFP (), for the purpose of aiding the GOA. The goal is to improve the robustness of predicted PPI pairs by removing the false positive pairs and sustaining as much true positive pairs as possible, thus achieving a high confidence level of PPI datasets. The PPI-Filter has been proven to be applicable based on the satisfactory results obtained using signal-to-noise ratio (SNR) and strength measurements that were applied on different computational PPI prediction methods.

Item Type:Article
Uncontrolled Keywords:protein protein interaction, signal to noise ratio, genomic
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:26214
Deposited By: Narimah Nawil
Deposited On:28 Jun 2012 10:01
Last Modified:30 Nov 2018 14:23

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