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SIAMCAT: user-friendly and versatile machine learning workflows for statistically rigorous microbiome analyses
View ORCID ProfileJakob Wirbel, Konrad Zych, View ORCID ProfileMorgan Essex, View ORCID ProfileNicolai Karcher, View ORCID ProfileEce Kartal, View ORCID ProfileGuillem Salazar, Peer Bork, Shinichi Sunagawa, Georg Zeller
doi: https://doi.org/10.1101/2020.02.06.931808
Jakob Wirbel
1Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
Konrad Zych
2Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
Morgan Essex
3Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
Nicolai Karcher
4Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
Ece Kartal
5Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
Guillem Salazar
6Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Zürich 8093, Switzerland
Peer Bork
7Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany
Shinichi Sunagawa
8Department of Biology, Institute of Microbiology and Swiss Institute of Bioinformatics, ETH Zürich, Zürich 8093, Switzerland
Georg Zeller
9Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstr 1, 69117 Heidelberg, Germany
Posted February 06, 2020.
SIAMCAT: user-friendly and versatile machine learning workflows for statistically rigorous microbiome analyses
Jakob Wirbel, Konrad Zych, Morgan Essex, Nicolai Karcher, Ece Kartal, Guillem Salazar, Peer Bork, Shinichi Sunagawa, Georg Zeller
bioRxiv 2020.02.06.931808; doi: https://doi.org/10.1101/2020.02.06.931808
SIAMCAT: user-friendly and versatile machine learning workflows for statistically rigorous microbiome analyses
Jakob Wirbel, Konrad Zych, Morgan Essex, Nicolai Karcher, Ece Kartal, Guillem Salazar, Peer Bork, Shinichi Sunagawa, Georg Zeller
bioRxiv 2020.02.06.931808; doi: https://doi.org/10.1101/2020.02.06.931808
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