Enhancing the application of machine learning models to microbiome data with 
endoR

Ruaud, A; Pfister, N; Ley, RE; Youngblut, ND

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Enhancing the application of machine learning models to microbiome data with endoR

MPS-Authors

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Ruaud, A
Department Microbiome Science, Max Planck Institute for Biology Tübingen, Max Planck Society;

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Ley, RE
Department Microbiome Science, Max Planck Institute for Biology Tübingen, Max Planck Society;

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Youngblut, ND
Department Microbiome Science, Max Planck Institute for Biology Tübingen, Max Planck Society;

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https://www.cell-symposia.com/infectionbiology-2023/conference-program.asp
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Citation

Ruaud, A., Pfister, N., Ley, R., & Youngblut, N. (2023). Enhancing the application of machine learning models to microbiome data with endoR. Poster presented at Cell Symposia: Infection Biology in the Age of the Microbiome, Paris, France.

Cite as: https://hdl.handle.net/21.11116/0000-000D-4BAA-0

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