LGCA-VHPPI: A local-global residue context aware viral-host protein-protein interaction predictor.

ABSTRACT: Viral-host protein protein interaction (PPI) analysis is essential to decode the molecular mechanism of viral pathogen and host immunity processes which eventually help to control viral diseases and optimize therapeutics. The state-of-the-art viral-host PPI predictor leverages unsupervised embedding learning technique (doc2vec) to generate statistical representations of viral-host protein sequences and a Random Forest classifier for interaction prediction. However, doc2vec approach generates the statistical representations of viral-host protein sequences by merely modelling the local context of residues which only partially captures residue semantics. The paper in hand proposes a novel technique for generating better statistical representations of viral and host protein sequences based on

SUBMITTER: Asim MN 

PROVIDER: S-EPMC9255777 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature