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Single-cell gene expression profiling and cell state dynamics: collecting data, correlating data points and connecting the dots

Marr, Carsten, Zhou, Joseph X, Huang, Sui·2016·Current Opinion in Biotechnology
DOI 10.1016/j.copbio.2016.04.015PMC PMC5130334

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Metadata

Authors
Marr, C., Zhou, J. X., & Huang, S.
Venue
Current Opinion in Biotechnology
Publisher
Elsevier BV
Published
2016-06
Volume
39
Pages
207-214
ISSN
0958-1669
DOI
10.1016/j.copbio.2016.04.015
PMC
PMC5130334
Cited by
35
References
19
Language
en
Licence
  • www.elsevier.com/tdm/userlicense/1.0/ (tdm)
  • www.elsevier.com/legal/tdmrep-license (tdm)
Funders
  • German Science Foundation DFG
  • National Institutes of Health (R01GM987654)

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CoChat. (2026). Citation check: Single-cell gene expression profiling and cell state dynamics: collecting data, correlating data points and connecting the dots. https://app.cochat.ai/papers/10.1016/j.copbio.2016.04.015
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Marr, C., Zhou, J. X., & Huang, S. (2016). Single-cell gene expression profiling and cell state dynamics: collecting data, correlating data points and connecting the dots. Current Opinion in Biotechnology. https://doi.org/10.1016/j.copbio.2016.04.015

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.