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Iterative transfer learning with neural network for clustering and cell type classification in single-cell RNA-seq analysis
Clustering and cell type classification are important steps in single-cell RNA-seq (scRNA-seq) analysis. As more and more scRNA-seq data are becoming available, supervised cell type classification methods that utilize external well-annotated source data start to gain popularity over unsupervised clu...
Tallennettuna:
| Julkaisussa: | Nat Mach Intell |
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| Päätekijät: | , , , , , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
2020
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8009055/ https://ncbi.nlm.nih.gov/pubmed/33817554 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s42256-020-00233-7 |
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