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Uncovering the key dimensions of high-throughput biomolecular data using deep learning
Recent advances in high-throughput single-cell RNA-seq have enabled us to measure thousands of gene expression levels at single-cell resolution. However, the transcriptomic profiles are high-dimensional and sparse in nature. To address it, a deep learning framework based on auto-encoder, termed Deep...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7261195/ https://www.ncbi.nlm.nih.gov/pubmed/32232416 http://dx.doi.org/10.1093/nar/gkaa191 |