Protein-Protein Interactions Efficiently Modeled by Residue Cluster Classes.

ABSTRACT: Predicting protein-protein interactions (PPI) represents an important challenge in structural bioinformatics. Current computational methods display different degrees of accuracy when predicting these interactions. Different factors were proposed to help improve these predictions, including choosing the proper descriptors of proteins to represent these interactions, among others. In the current work, we provide a representative protein structure that is amenable to PPI classification using machine learning approaches, referred to as residue cluster classes. Through sampling and optimization, we identified the best algorithm-parameter pair to classify PPI from more than 360 different training sets. We tested these classifiers against PPI datasets that were not included in the training set bu

SUBMITTER: Poot Velez AH 

PROVIDER: S-EPMC7370293 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature