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DeepToA: An Ensemble Deep-Learning Approach to Predicting the Theater of Activity of a Microbiome
Wenhuan Zeng, Anupam Gautam, Daniel H. Huson
doi: https://doi.org/10.1101/2022.04.04.486969
Wenhuan Zeng
1Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, 72076, Germany
Anupam Gautam
1Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, 72076, Germany
2International Max Planck Research School “From Molecules to Organisms”, Max Planck Institute for Biology Tübingen, Max-Planck-Ring 5, Tübingen, 72076, Germany
Daniel H. Huson
1Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, 72076, Germany
2International Max Planck Research School “From Molecules to Organisms”, Max Planck Institute for Biology Tübingen, Max-Planck-Ring 5, Tübingen, 72076, Germany
3Cluster of Excellence: Controlling Microbes to Fight Infection, Tübingen, Germany
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Posted April 05, 2022.
DeepToA: An Ensemble Deep-Learning Approach to Predicting the Theater of Activity of a Microbiome
Wenhuan Zeng, Anupam Gautam, Daniel H. Huson
bioRxiv 2022.04.04.486969; doi: https://doi.org/10.1101/2022.04.04.486969
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