Cross-attention graph neural networks for inferring gene regulatory networks with skewed degree distribution

Cross-attention graph neural networks for inferring gene regulatory networks with skewed degree distribution

Abstract Background Inferring Gene Regulatory Networks (GRNs) from gene expression data is a pivotal challenge in systems biology. Most existing methods fail to consider the skewed degree distribution of genes, complicating the application of directed graph embedding methods. Results The Cross-Atten...

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Bibliographic Details
Main Authors: Jiaqi Xiong, Nan Yin, Shiyang Liang, Haoyang Li, Yingxu Wang, Duo Ai, Jingjie Wang
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Bioinformatics
Subjects:
Gene regulatory network
Direct graph embedding
Cross attention network
Online Access:https://doi.org/10.1186/s12859-025-06186-1
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