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Integrating single-cell transcriptomic data across different conditions, technologies, and species
Computational single-cell RNA-seq (scRNA-seq) methods have been successfully applied to experiments representing a single condition, technology, or species to discover and define cellular phenotypes. However, identifying subpopulations of cells that are present across multiple datasets remains chall...
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| 出版年: | Nat Biotechnol |
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| 主要な著者: | , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2018
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6700744/ https://ncbi.nlm.nih.gov/pubmed/29608179 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/nbt.4096 |
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