Molecular complex detection in protein interaction networks through reinforcement learning.

ABSTRACT:

Background

Proteins often assemble into higher-order complexes to perform their biological functions. Such protein-protein interactions (PPI) are often experimentally measured for pairs of proteins and summarized in a weighted PPI network, to which community detection algorithms can be applied to define the various higher-order protein complexes. Current methods include unsupervised and supervised approaches, often assuming that protein complexes manifest only as dense subgraphs. Utilizing supervised approaches, the focus is not on how to find them in a network, but only on learning which subgraphs correspond to complexes, currently solved using heuristics. However, learning to walk trajectories on a network to identify protein complexes leads naturally to a reinforcement learning

SUBMITTER: Palukuri MV 

PROVIDER: S-EPMC10394916 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature