NPI-WGNN: A Weighted Graph Neural Network Leveraging Centrality Measures and High-Order Common Neighbor Similarity for Accurate ncRNA–Protein Interaction Prediction

NPI-WGNN: A Weighted Graph Neural Network Leveraging Centrality Measures and High-Order Common Neighbor Similarity for Accurate ncRNA–Protein Interaction Prediction

Predicting ncRNA–protein interactions (NPIs) is essential for understanding regulatory roles in cellular processes and disease mechanisms, yet experimental methods are costly and time-consuming. In this study, we propose NPI-WGNN, a novel weighted graph neural network model designed to enhance NPI p...

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Bibliographic Details
Main Authors: Fatemeh Khoushehgir, Zahra Noshad, Morteza Noshad, Sadegh Sulaimany
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Analytics
Subjects:
ncRNA–protein interaction
weighted graph neural network
link prediction
topological features
Online Access:https://www.mdpi.com/2813-2203/3/4/27
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https://www.mdpi.com/2813-2203/3/4/27

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