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Deep learning–based cell composition analysis from tissue expression profiles
We present Scaden, a deep neural network for cell deconvolution that uses gene expression information to infer the cellular composition of tissues. Scaden is trained on single-cell RNA sequencing (RNA-seq) data to engineer discriminative features that confer robustness to bias and noise, making comp...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Association for the Advancement of Science
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7439569/ https://www.ncbi.nlm.nih.gov/pubmed/32832661 http://dx.doi.org/10.1126/sciadv.aba2619 |