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
Gespeichert in:
| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2017
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| In: |
Bioinformatics
Year: 2016, Jahrgang: 33, Heft: 2, Pages: 235-242 |
| ISSN: | 1367-4811 |
| DOI: | 10.1093/bioinformatics/btw607 |
| Online-Zugang: | 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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| Verfasserangaben: | Chunxuan Shao and Thomas Höfer |
| Zusammenfassung: | AbstractMotivation. Single-cell transcriptome data provide unprecedented resolution to study heterogeneity in cell populations and present a challenge for unsu |
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| Beschreibung: | Advance access publication date: 23 September 2016 Gesehen am 27.07.2018 |
| Beschreibung: | Online Resource |
| ISSN: | 1367-4811 |
| DOI: | 10.1093/bioinformatics/btw607 |