Back to search

Article

HGNNPIP: A Hybrid Graph Neural Network framework for Protein-protein Interaction Prediction

2023-12-11

Abstract excerpt

A deep understanding of Protein-protein interactions (PPIs) can provide comprehensive insights into many biological functions, thereby facilitating drug target identification and novel therapeutic design. Recent developments in artificial intelligence (AI)-driven computational methods have enabled the discovery of previously uncharacterized PPIs from large-scale interactome datasets. Almost all existing machine le...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
53b4a65a-8b0c-57c5-b522-6380bec1d9a9
DOI
10.1101/2023.12.10.571021
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
HGNNPIP: A Hybrid Graph Neural Network framework for Protein-protein Interaction PredictionDOI 10.1101/2023.12.10.571021
Select a neighboring publication to make it the new centre.