Open AccessPC2P: parameter-free network-based prediction of protein complexes
Author(s) -
Sara Omranian,
Aleksandra Angeleska,
Zoran Nikoloski
Publication year - 2021
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btaa1089
Subject(s) - partition (number theory) , computer science , cluster analysis , bipartite graph , key (lock) , theoretical computer science , algorithm , artificial intelligence , combinatorics , mathematics , graph , computer security
Prediction of protein complexes from protein-protein interaction (PPI) networks is an important problem in systems biology, as they control different cellular functions. The existing solutions employ algorithms for network community detection that identify dense subgraphs in PPI networks. However, gold standards in yeast and human indicate that protein complexes can also induce sparse subgraphs, introducing further challenges in protein complex prediction.