A three-phase method for identifying functionally related protein groups in weighted PPI networks

Comput Biol Chem. 2020 Jun:86:107246. doi: 10.1016/j.compbiolchem.2020.107246. Epub 2020 Mar 5.

Abstract

Identifying significant protein groups is of great importance for further understanding protein functions. This paper introduces a novel three-phase heuristic method for identifying such groups in weighted PPI networks. In the first phase a variable neighborhood search (VNS) algorithm is applied on a weighted PPI network, in order to support protein complexes by adding a minimum number of new PPIs. In the second phase proteins from different complexes are merged into larger protein groups. In the third phase these groups are expanded by a number of 2-level neighbor proteins, favoring proteins that have higher average gene co-expression with the base group proteins. Experimental results show that: (i) the proposed VNS algorithm outperforms the existing approach described in literature and (ii) the above-mentioned three-phase method identifies protein groups with very high statistical significance.

Keywords: Gene co-expression; Protein groups; Variable neighborhood search; Weighted PPI networks.

MeSH terms

  • Computational Biology / methods*
  • Protein Interaction Mapping / methods*
  • Protein Interaction Maps
  • Proteins / metabolism

Substances

  • Proteins