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The performance of deep generative models for learning joint embeddings of single-cell multi-omics data
Recent extensions of single-cell studies to multiple data modalities raise new questions regarding experimental design. For example, the challenge of sparsity in single-omics data might be partly resolved by compensating for missing information across modalities. In particular, deep learning approac...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643784/ https://www.ncbi.nlm.nih.gov/pubmed/36387277 http://dx.doi.org/10.3389/fmolb.2022.962644 |