Original scientific paper

https://doi.org/10.17559/TV-20180829122435

Link Prediction Based on Extended Local Path Gain in Protein-Protein Interaction Network

Huiyan Sun ; Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, #2699 Qianjin St, Changchun, 130012, China
Yanchun Liang ; Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, #2699 Qianjin St, Changchun, 130012, China
Yan Wang orcid.org/0000-0002-4751-0708 ; Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, #2699 Qianjin St, Changchun, 130012, China
Liang Chen orcid.org/0000-0001-6644-477X ; University of Macau, Taipa, Macau S.A.R., 999078, China
Wei Du ; Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, #2699 Qianjin St, Changchun, 130012, China
Yuexu Jiang ; University of Missouri, Columbia, MO 65211, USA
Xiaohu Shi orcid.org/0000-0002-5115-8137 ; Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, #2699 Qianjin St, Changchun, 130012, China

Abstract

Protein–protein interaction (PPI) plays key role in each cellular process of any living cell, however, almost all organisms’ PPIs are still incomplete. In this study, we firstly proposed a computational method Extended Local Path (ELP), which estimated links’ existence likelihood by integrating all their neighbours’ local paths in the network. In addition, on this basis, we extended it to Extended Local Path Gain (ELPG), which estimated gain effect when adding or deleting one potential link to the network. Applying both ELPG and ELP methods and other four recognized outstanding methods on four public PPI data of Yeast, E. coli, Fruit fly and Mouse, we demonstrated that ELPG and ELP obtained better performance under two standard measures: area under curve (AUC) and Precision. Besides, ELP and ELPG were identified as the best features for classifying existing and unknown links by using support vector machine-recursive feature elimination (SVM-RFE) for feature selection.

Keywords

Extended Local Path (ELP); Extended Local Path Gain (ELPG); Link prediction; Protein–Protein Interaction (PPI)

Hrčak ID:

217105

URI

https://hrcak.srce.hr/217105

Publication date:

16.2.2019.

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