Protein-protein interface hot spots prediction based on a hybrid feature selection strategy.

ABSTRACT:

Background

Hot spots are interface residues that contribute most binding affinity to protein-protein interaction. A compact and relevant feature subset is important for building machine learning methods to predict hot spots on protein-protein interfaces. Although different methods have been used to detect the relevant feature subset from a variety of features related to interface residues, it is still a challenge to detect the optimal feature subset for building the final model.

Results

In this study, three different feature selection methods were compared to propose a new hybrid feature selection strategy. This new strategy was proved to effectively reduce the feature space when we were building the prediction models for identifying hotspot residues. It was tested on eighty

SUBMITTER: Qiao Y 

PROVIDER: S-EPMC5769548 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature