Enhancing Missense Variant Pathogenicity Prediction with MissenseNet: Integrating Structural Insights and ShuffleNet-Based Deep Learning Techniques

Enhancing Missense Variant Pathogenicity Prediction with MissenseNet: Integrating Structural Insights and ShuffleNet-Based Deep Learning Techniques

The classification of missense variant pathogenicity continues to pose significant challenges in human genetics, necessitating precise predictions of functional impacts for effective disease diagnosis and personalized treatment strategies. Traditional methods, often compromised by suboptimal feature...

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Bibliographic Details
Main Authors: Jing Liu, Yingying Chen, Kai Huang, Xiao Guan
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:Biomolecules
Subjects:
missense variant
pathogenicity prediction
deep learning
attention mechanisms
Online Access:https://www.mdpi.com/2218-273X/14/9/1105
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