Unsupervised construction of computational graphs for gene expression data with explicit structural inductive biases

MOTIVATION: Gene expression data are commonly used at the intersection of cancer research and machine learning for better understanding of the molecular status of tumour tissue. Deep learning predictive models have been employed for gene expression data due to their ability to scale and remove the n...

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Detalles Bibliográficos
Autores principales: Scherer, Paul, Trębacz, Maja, Simidjievski, Nikola, Viñas, Ramon, Shams, Zohreh, Terre, Helena Andres, Jamnik, Mateja, Liò, Pietro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8826027/
https://www.ncbi.nlm.nih.gov/pubmed/34888618
http://dx.doi.org/10.1093/bioinformatics/btab830

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8826027/
https://www.ncbi.nlm.nih.gov/pubmed/34888618
http://dx.doi.org/10.1093/bioinformatics/btab830

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