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Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
Simon Höllerer, Laetitia Papaxanthos, Anja Cathrin Gumpinger, Katrin Fischer, Christian Beisel, Karsten Borgwardt, Yaakov Benenson, Markus Jeschek
doi: https://doi.org/10.1101/2020.01.23.915405
Simon Höllerer
1Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
Laetitia Papaxanthos
1Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
2Swiss Institute of Bioinformatics, Switzerland
Anja Cathrin Gumpinger
1Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
2Swiss Institute of Bioinformatics, Switzerland
Katrin Fischer
1Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
Christian Beisel
1Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
Karsten Borgwardt
1Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
2Swiss Institute of Bioinformatics, Switzerland
Yaakov Benenson
1Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
Markus Jeschek
1Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
Article usage
Posted January 24, 2020.
Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
Simon Höllerer, Laetitia Papaxanthos, Anja Cathrin Gumpinger, Katrin Fischer, Christian Beisel, Karsten Borgwardt, Yaakov Benenson, Markus Jeschek
bioRxiv 2020.01.23.915405; doi: https://doi.org/10.1101/2020.01.23.915405
Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
Simon Höllerer, Laetitia Papaxanthos, Anja Cathrin Gumpinger, Katrin Fischer, Christian Beisel, Karsten Borgwardt, Yaakov Benenson, Markus Jeschek
bioRxiv 2020.01.23.915405; doi: https://doi.org/10.1101/2020.01.23.915405
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