The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning
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Zheng, G. X. Y., Terry, J. M., Belgrader, P., Ryvkin, P., Bent, Z. W., Wilson, R., Ziraldo, S. B., Wheeler, T. D., McDermott, G. P., Zhu, J., et al. (2017) · Nature Communications · doi:10.1038/ncomms14049 · Cited by 7,353
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Clustering by Passing Messages Between Data Points
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Cited by
Integrating single-cell transcriptomic data across different conditions, technologies, and species
Butler, A., Hoffman, P., Smibert, P., Papalexi, E., & Satija, R. (2018) · Nature Biotechnology · doi:10.1038/nbt.4096 · Cited by 13,174
Applications of machine learning in drug discovery and development
Vamathevan, J., Clark, D., Czodrowski, P., Dunham, I., Ferran, E., Lee, G., Li, B., Madabhushi, A., Shah, P., Spitzer, M., et al. (2019) · Nature Reviews Drug Discovery · doi:10.1038/s41573-019-0024-5 · Cited by 3,228
Deep generative modeling for single-cell transcriptomics
Lopez, R., Regier, J., Cole, M. B., Jordan, M. I., & Yosef, N. (2018) · Nature Methods · doi:10.1038/s41592-018-0229-2 · Cited by 2,530
Current best practices in single-cell RNA-seq analysis: a tutorial
Luecken, M. D., & Theis, F. J. (2019) · Molecular Systems Biology · doi:10.15252/msb.20188746 · Cited by 2,231
Wolf, F. A., Hamey, F. K., Plass, M., Solana, J., Dahlin, J. S., Göttgens, B., Rajewsky, N., Simon, L., & Theis, F. J. (2019) · Genome Biology · doi:10.1186/s13059-019-1663-x · Cited by 1,698
Metadata
- Authors
- Wang, B., Zhu, J., Pierson, E., Ramazzotti, D., & Batzoglou, S.
- Venue
- Nature Methods
- Published
- 2017-03-06
- Volume
- 14
- Issue
- 4
- Pages
- 414-416
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2953251392
- Cited by
- 706
- References
- 42
- FWCI
- 25.33
- Type
- journal article
- Language
- en
- Open access
- green
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- Wang, B., Zhu, J., Pierson, E., Ramazzotti, D., & Batzoglou, S. (2017). Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning. Nature Methods. https://doi.org/10.1038/nmeth.4207
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