GSLAlign: community detection and local PPI network alignment

Abstract

High throughput protein–protein interaction (PPI) profiling and computational techniques have resulted in generating a large amount of PPI network data. The study of PPI networks helps in understanding the biological processes of the proteins. The comparative study of the PPI networks helps in identifying the conserved interactions across the species. This article presents a novel local PPI network aligner ‘GSLAlign’ that consists of two stages. It first detects the communities from the PPI networks by applying the GraphSAGE algorithm using gene expression data. In the second stage, the detected communities are aligned using a community aligner that is based on protein sequence similarity. The community detection algorithm produces more separable and biologically accurate communities as compared to previous community detection algorithms. Moreover, the proposed community alignment algorithm achieves 3–8% better results in terms of semantic similarity as compared to previous local aligners. The average connectivity and coverage of the proposed algorithm are also better than the existing aligners.

Communicated by Ramaswamy H. Sarma

Keywords:

• Protein–protein interaction
• local PPI network alignment
• GraphSAGE
• gene expression
• community detection
• sequence similarity

Authors’ contributions

UA and HN designed the research. UA implements the research. UA and HN analyze the results and write the manuscript. Both authors proofread the article.

Ethical statement

This article is prepared according to the rules of ethical organizations. This article did not include any animal or human testing/involvement. Moreover, this article is an original article.

Disclosure statement

We have no conflict of interest (financial or non-financial).

Additional information

Funding

This work has been supported by a grant to establish Precision Medicine Lab under the umbrella of the National Center in Big Data and Cloud Computing from the Higher Education of Pakistan.