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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...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2023
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| Materias: | |
| 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 |