Efficient link prediction in the protein-protein interaction network using topological information in a generative adversarial network machine learning model.

ABSTRACT:

Background

The investigation of possible interactions between two proteins in intracellular signaling is an expensive and laborious procedure in the wet-lab, therefore, several in silico approaches have been implemented to narrow down the candidates for future experimental validations. Reformulating the problem in the field of network theory, the set of proteins can be represented as the nodes of a network, while the interactions between them as the edges. The resulting protein-protein interaction (PPI) network enables the use of link prediction techniques in order to discover new probable connections. Therefore, here we aimed to offer a novel approach to the link prediction task in PPI networks, utilizing a generative machine learning model.

Results

We created a tool that c

SUBMITTER: Balogh OM 

PROVIDER: S-EPMC8858570 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature