GIFT: Guided and Interpretable Factorization for Tensors with an application to large-scale multi-platform cancer analysis

MOTIVATION: Given multi-platform genome data with prior knowledge of functional gene sets, how can we extract interpretable latent relationships between patients and genes? More specifically, how can we devise a tensor factorization method which produces an interpretable gene factor matrix based on...

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Detalles Bibliográficos
Autores principales: Lee, Jungwoo, Oh, Sejoon, Sael, Lee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6289137/
https://www.ncbi.nlm.nih.gov/pubmed/29931238
http://dx.doi.org/10.1093/bioinformatics/bty490

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6289137/
https://www.ncbi.nlm.nih.gov/pubmed/29931238
http://dx.doi.org/10.1093/bioinformatics/bty490

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