Author

Vincent Fortuin

ETH ZurichORCID 0000-0002-0640-2671Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Organism:E. coli· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

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Eirini ArvanitiiD· 1 shared Manfred ClaasseniD· 1 shared Max HorniD· 1 shared Stefan GanschaiD· 1 shared

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Eirini ArvanitiORCID

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1 paper

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Systems BiologybioRxivPreprintJun 27, 2018

Supervised learning on synthetic data for reverse engineering gene regulatory networks from experimental time-series

Stefan Ganscha, Vincent Fortuin, Max Horn…·Manfred Claassen

This paper introduces a supervised learning method using synthetic data to reconstruct gene regulatory networks from experimental time-series, showing superior performance compared to unsupervised methods.

2 citations

E. colibulk RNA-seq

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