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Random forest based similarity learning for single cell RNA sequencing data
MOTIVATION: Genome-wide transcriptome sequencing applied to single cells (scRNA-seq) is rapidly becoming an assay of choice across many fields of biological and biomedical research. Scientific objectives often revolve around discovery or characterization of types or sub-types of cells, and therefore...
Tallennettuna:
| Julkaisussa: | Bioinformatics |
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| Päätekijät: | , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Oxford University Press
2018
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6022547/ https://ncbi.nlm.nih.gov/pubmed/29950006 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/bty260 |
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