Robust classification of single-cell transcriptome data by nonnegative matrix factorization
AbstractMotivation. Single-cell transcriptome data provide unprecedented resolution to study heterogeneity in cell populations and present a challenge for unsu
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| Main Authors: | , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
2017
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| In: |
Bioinformatics
Year: 2016, Volume: 33, Issue: 2, Pages: 235-242 |
| ISSN: | 1367-4811 |
| DOI: | 10.1093/bioinformatics/btw607 |
| Online Access: | Verlag, Volltext: http://dx.doi.org/10.1093/bioinformatics/btw607 Verlag, Volltext: https://academic.oup.com/bioinformatics/article/33/2/235/2525715 
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| Author Notes: | Chunxuan Shao and Thomas Höfer |
| Summary: | AbstractMotivation. Single-cell transcriptome data provide unprecedented resolution to study heterogeneity in cell populations and present a challenge for unsu |
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| Item Description: | Advance access publication date: 23 September 2016 Gesehen am 27.07.2018 |
| Physical Description: | Online Resource |
| ISSN: | 1367-4811 |
| DOI: | 10.1093/bioinformatics/btw607 |