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Supervised learning on synthetic data for reverse engineering gene regulatory networks from experimental time-series
Stefan Ganscha, Vincent Fortuin, Max Horn, Eirini Arvaniti, Manfred Claassen
doi: https://doi.org/10.1101/356477
Stefan Ganscha
1Institute of Molecular Systems Biology, ETH Zürich
2Life Science Graduate School Zürich
3Swiss Institute of Bioinformatics
Vincent Fortuin
1Institute of Molecular Systems Biology, ETH Zürich
Max Horn
1Institute of Molecular Systems Biology, ETH Zürich
Eirini Arvaniti
1Institute of Molecular Systems Biology, ETH Zürich
2Life Science Graduate School Zürich
3Swiss Institute of Bioinformatics
Manfred Claassen
1Institute of Molecular Systems Biology, ETH Zürich
3Swiss Institute of Bioinformatics
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Posted June 27, 2018.
Supervised learning on synthetic data for reverse engineering gene regulatory networks from experimental time-series
Stefan Ganscha, Vincent Fortuin, Max Horn, Eirini Arvaniti, Manfred Claassen
bioRxiv 356477; doi: https://doi.org/10.1101/356477
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