PAUSE: principled feature attribution for unsupervised gene expression analysis

As interest in using unsupervised deep learning models to analyze gene expression data has grown, an increasing number of methods have been developed to make these models more interpretable. These methods can be separated into two groups: post hoc analyses of black box models through feature attribu...

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Detalles Bibliográficos
Autores principales: Janizek, Joseph D., Spiro, Anna, Celik, Safiye, Blue, Ben W., Russell, John C., Lee, Ting-I, Kaeberlin, Matt, Lee, Su-In
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10114348/
https://www.ncbi.nlm.nih.gov/pubmed/37076856
http://dx.doi.org/10.1186/s13059-023-02901-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10114348/
https://www.ncbi.nlm.nih.gov/pubmed/37076856
http://dx.doi.org/10.1186/s13059-023-02901-4

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