MetaSEM: Gene Regulatory Network Inference from Single-Cell RNA Data by Meta-Learning

Regulators in gene regulatory networks (GRNs) are crucial for identifying cell states. However, GRN inference based on scRNA-seq data has several problems, including high dimensionality and sparsity, and requires more label data. Therefore, we propose a meta-learning GRN inference framework to ident...

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Detalles Bibliográficos
Autores principales: Zhang, Yongqing, Wang, Maocheng, Wang, Zixuan, Liu, Yuhang, Xiong, Shuwen, Zou, Quan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9916710/
https://www.ncbi.nlm.nih.gov/pubmed/36768917
http://dx.doi.org/10.3390/ijms24032595

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9916710/
https://www.ncbi.nlm.nih.gov/pubmed/36768917
http://dx.doi.org/10.3390/ijms24032595

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