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Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis
BACKGROUND: Single-cell RNA-sequencing (scRNA-seq) is a transformative technology, allowing global transcriptomes of individual cells to be profiled with high accuracy. An essential task in scRNA-seq data analysis is the identification of cell types from complex samples or tissues profiled in an exp...
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| 出版年: | BMC Bioinformatics |
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| 主要な著者: | , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BioMed Central
2019
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6929272/ https://ncbi.nlm.nih.gov/pubmed/31870278 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-019-3179-5 |
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