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Joris Cadow

Showing results (1-10 of 6) with videos related to

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NPJ Systems Biology and Applications|March 12, 2019
PIMKL: Pathway-Induced Multiple Kernel LearningMatteo Manica, Joris Cadow, Roland Mathis, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|October 7, 2024
Digital Fingerprinting of Complex Liquids Using a Reconfigurable Multi-Sensor System with Foundation ModelsGianmarco Gabrieli, Matteo Manica, Joris Cadow-Gossweiler, et al.
Nucleic Acids Research|May 14, 2020
PaccMann: a web service for interpretable anticancer compound sensitivity predictionJoris Cadow, Jannis Born, Matteo Manica, et al.
Iscience|April 14, 2021
PaccMann<sup>RL</sup>: De novo generation of hit-like anticancer molecules from transcriptomic data via reinforcement learningJannis Born, Matteo Manica, Ali Oskooei, et al.
Bioinformatics (Oxford, England)|July 12, 2021
On the feasibility of deep learning applications using raw mass spectrometry dataJoris Cadow, Matteo Manica, Roland Mathis, et al.
Bioinformatics (Oxford, England)|November 26, 2020
COSIFER: a Python package for the consensus inference of molecular interaction networksMatteo Manica, Charlotte Bunne, Roland Mathis, et al.
Pageof 1

Showing results (1-10 of 6) with videos related to

Sort By:
Pageof 1
NPJ Systems Biology and Applications|March 12, 2019
PIMKL: Pathway-Induced Multiple Kernel LearningMatteo Manica, Joris Cadow, Roland Mathis, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|October 7, 2024
Digital Fingerprinting of Complex Liquids Using a Reconfigurable Multi-Sensor System with Foundation ModelsGianmarco Gabrieli, Matteo Manica, Joris Cadow-Gossweiler, et al.
Nucleic Acids Research|May 14, 2020
PaccMann: a web service for interpretable anticancer compound sensitivity predictionJoris Cadow, Jannis Born, Matteo Manica, et al.
Iscience|April 14, 2021
PaccMann<sup>RL</sup>: De novo generation of hit-like anticancer molecules from transcriptomic data via reinforcement learningJannis Born, Matteo Manica, Ali Oskooei, et al.
Bioinformatics (Oxford, England)|July 12, 2021
On the feasibility of deep learning applications using raw mass spectrometry dataJoris Cadow, Matteo Manica, Roland Mathis, et al.
Bioinformatics (Oxford, England)|November 26, 2020
COSIFER: a Python package for the consensus inference of molecular interaction networksMatteo Manica, Charlotte Bunne, Roland Mathis, et al.
Pageof 1