Self-supervised graph representation learning integrates multiple molecular networks and decodes gene-disease relationships

Leveraging molecular networks to discover disease-relevant modules is a long-standing challenge. With the accumulation of interactomes, there is a pressing need for powerful computational approaches to handle the inevitable noise and context-specific nature of biological networks. Here, we introduce...

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Detalles Bibliográficos
Autores principales: Wang, Yi, Sun, Zijun, He, Qiushun, Li, Jiwei, Ni, Ming, Yang, Meng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9868676/
https://www.ncbi.nlm.nih.gov/pubmed/36699743
http://dx.doi.org/10.1016/j.patter.2022.100651

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9868676/
https://www.ncbi.nlm.nih.gov/pubmed/36699743
http://dx.doi.org/10.1016/j.patter.2022.100651

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