Most proteins perform their biological function by interacting with themselves or other
molecules. Thus, one may obtain biological insights into protein functions, disease …

Protein–protein interactions (PPIs) are essential in the regulation of biological functions and
cell events, therefore understanding PPIs have become a key issue to understanding the …

Deep learning, a potent branch of artificial intelligence, is steadily leaving its transformative
imprint across multiple disciplines. Within computational biology, it is expediting progress in …

Proteins mainly perform their functions by interacting with other proteins. Protein–protein
interactions underpin various biological activities such as metabolic cycles, signal …

This survey paper provides a comprehensive analysis of various Deep Learning (DL)
techniques and algorithms for detecting protein-protein interactions (PPIs). It examines the …

The prominence of protein–protein interactions (PPIs) in system biology with diverse
biological procedures has become the topic to discuss because it acts as a fundamental part …

Background: The use of machine learning models in sequence-based Protein-Protein
Interaction prediction typically requires the conversion of amino acid sequences into feature …

Deep Forest employs forest structures and leverages deep architecture to learn feature
vector information adaptively. However, deep forest-based models have limitations such as …

Identifying protein-protein interactions (PPIs) represents a challenging research problem in
computational biology. Even though machine learning methods have significantly advanced …

Protein–protein interactions (PPIs) are known to play a crucial role in system biology by
predicting the protein function of a given target. Machine learning (ML) could provide …