Machine Learning for Deciphering Cell Heterogeneity and Gene Regulation

Scherer, Michael; Schmidt, Florian; Lazareva, Olga; Walter, Jörn; Baumbach, Jan; Schulz, Marcel Holger; List, Markus

doi:10.1038/s43588-021-00038-7

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Machine Learning for Deciphering Cell Heterogeneity and Gene Regulation

Scherer, M., Schmidt, F., Lazareva, O., Walter, J., Baumbach, J., Schulz, M. H., et al. (2021). Machine Learning for Deciphering Cell Heterogeneity and Gene Regulation. Nature Computational Science, 1. doi:10.1038/s43588-021-00038-7.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0008-2A4A-7 Version Permalink: https://hdl.handle.net/21.11116/0000-0008-2A4B-6

Genre: Journal Article

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Creators:
Scherer, Michael¹, Author
Schmidt, Florian², Author
Lazareva, Olga², Author
Walter, Jörn¹, Author
Baumbach, Jan², Author
Schulz, Marcel Holger², Author
List, Markus², Author

Affiliations:
1Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society, ou_40046
2External Organizations, ou_persistent22

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Language(s): eng - English

Dates: Published Online: 2021

Publication Status: Published online

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Identifiers: BibTex Citekey: Scherer2021
DOI: 10.1038/s43588-021-00038-7

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Title: Nature Computational Science

Source Genre: Journal

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Publ. Info: London : Nature Research

Pages: 9 p. Volume / Issue: 1 Sequence Number: - Start / End Page: - Identifier: ISSN: 2662-8457