Predicting Protein-Protein Interactions by Convolutional Neural Network Model.

ABSTRACT: The study of protein-protein interactions (PPIs) is of significant importance for elucidating biological processes, clarifying pathological mechanisms, and promoting drug development. In this study, we proposed a method to predict PPIs based on protein sequence and gene sequence information, combined with convolutional neural networks (CNNs). First, we extracted three types of features from protein sequence: global physicochemical properties features of the protein sequence, local same type of amino acid position variation features, and protein evolutionary conservation features; simultaneously, we extracted single nucleotide frequency and positional features, dinucleotide frequency features, and trinucleotide frequency features from the corresponding gene sequence. During the feature extr

SUBMITTER: Shi S 

PROVIDER: S-EPMC12938199 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature