Super.Complex: A supervised machine learning pipeline for molecular complex detection in protein-interaction networks.

ABSTRACT: Characterization of protein complexes, i.e. sets of proteins assembling into a single larger physical entity, is important, as such assemblies play many essential roles in cells such as gene regulation. From networks of protein-protein interactions, potential protein complexes can be identified computationally through the application of community detection methods, which flag groups of entities interacting with each other in certain patterns. Most community detection algorithms tend to be unsupervised and assume that communities are dense network subgraphs, which is not always true, as protein complexes can exhibit diverse network topologies. The few existing supervised machine learning methods are serial and can potentially be improved in terms of accuracy and scalability by using better-

SUBMITTER: Palukuri MV 

PROVIDER: S-EPMC8240683 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature