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Denoising Protein-Protein interaction network via variational graph auto-encoder for protein complex detection.

Heng Yao1,2,3, Jihong Guan1,2,3, Tianying Liu1,2,3

  • 1Department of Computer Science and Technology, Tongji University, 4800 Cao'an Road, Shanghai 201804, P. R. China.

Journal of Bioinformatics and Computational Biology
|July 24, 2020
PubMed
Summary

This study introduces a denoising method using variational graph auto-encoders to improve protein complex detection from protein-protein interaction networks (PINs). The approach reconstructs reliable PINs, significantly boosting detection accuracy and outperforming existing denoising techniques.

Keywords:
Protein–Protein Interaction Network (PIN)graph embeddingprotein complexvariational auto-encoder

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Area of Science:

  • Computational biology
  • Bioinformatics
  • Network science

Background:

  • Identifying protein complexes is crucial for understanding cellular functions and drug design.
  • Existing methods often struggle due to high false positive/negative rates in protein-protein interaction networks (PINs).

Purpose of the Study:

  • To develop a denoising approach for enhancing protein complex detection accuracy.
  • To improve the reliability of protein-protein interaction networks (PINs) for downstream analysis.

Main Methods:

  • Utilized a stacked graph convolutional network (GCN) to embed PINs into vector space.
  • Employed a variational graph auto-encoder for denoising, identifying and removing unreliable interactions.
  • Applied established complex detection algorithms (CPM, Coach, DPClus, GraphEntropy, IPCA, MCODE) on the reconstructed PINs.

Main Results:

  • The denoising approach significantly improved protein complex detection performance, with gains ranging from 5% to 200% on yeast and human PPI datasets.
  • The proposed method outperformed two existing denoising techniques (RWS, RedNemo) in most tested scenarios.
  • Empirical evaluations were conducted on multiple yeast and human PPI datasets against established complex benchmarks.

Conclusions:

  • Denoising protein-protein interaction networks (PINs) with variational graph auto-encoders is an effective strategy for enhancing protein complex detection.
  • The proposed method offers a robust and improved alternative to existing approaches for analyzing biological networks.