Gene regulatory network inference based on causal discovery integrating with graph neural network

Abstract Gene regulatory network (GRN) inference from gene expression data is a significant approach to understanding aspects of the biological system. Compared with generalized correlation‐based methods, causality‐inspired ones seem more rational to infer regulatory relationships. We propose GRINCD...

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Autors principals:	Ke Feng, Hongyang Jiang, Chaoyi Yin, Huiyan Sun
Format:	Artigo
Idioma:	Inglês
Publicat:	Wiley 2023-12-01
Col·lecció:	Quantitative Biology
Matèries:	causal discovery ensemble learning gene regulatory network inference gene regulatory networks graph neural network key regulators of disease development
Accés en línia:	https://doi.org/10.1002/qub2.26
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