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

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.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-4BAA-0 Version Permalink: https://hdl.handle.net/21.11116/0000-000D-4BAB-F
Genre: Poster

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https://www.cell-symposia.com/infectionbiology-2023/conference-program.asp (Table of contents)
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 Creators:
Ruaud, A1, Author                 
Pfister, N, Author
Ley, RE1, Author                 
Youngblut, ND1, Author                 
Affiliations:
1Department Microbiome Science, Max Planck Institute for Biology Tübingen, Max Planck Society, ou_3371684              

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 Dates: 2023-06
 Publication Status: Published online
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Title: Cell Symposia: Infection Biology in the Age of the Microbiome
Place of Event: Paris, France
Start-/End Date: 2023-06-07 - 2023-06-09

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Title: Cell Symposia: Infection Biology in the Age of the Microbiome
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: P1.36 Start / End Page: - Identifier: -