A Graph Feature Auto-Encoder for the prediction of unobserved node features on biological networks

A Graph Feature Auto-Encoder for the prediction of unobserved node features on biological networks

Abstract Background Molecular interaction networks summarize complex biological processes as graphs, whose structure is informative of biological function at multiple scales. Simultaneously, omics technologies measure the variation or activity of genes, proteins, or metabolites across individuals or...

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Bibliographic Details
Main Authors: Ramin Hasibi, Tom Michoel
Format: Article
Language:English
Published: BMC 2021-10-01
Series:BMC Bioinformatics
Subjects:
Gene regulatory networks
Gene expression
Graph neural networks
Graph representation learning
Molecular networks
Omics
Online Access:https://doi.org/10.1186/s12859-021-04447-3

Internet

https://doi.org/10.1186/s12859-021-04447-3

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