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Current Medicinal Chemistry
|
July 30, 2021
Trends in Deep Learning for Property-driven Drug Design
Jannis Born, Matteo Manica
Scientific Reports
|
November 6, 2019
Network-based Biased Tree Ensembles (NetBiTE) for Drug Sensitivity Prediction and Drug Sensitivity Biomarker Identification in Cancer
Ali Oskooei, Matteo Manica, Roland Mathis, et al.
NPJ Systems Biology and Applications
|
March 12, 2019
PIMKL: Pathway-Induced Multiple Kernel Learning
Matteo 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 Models
Gianmarco Gabrieli, Matteo Manica, Joris Cadow-Gossweiler, et al.
Journal of Chemical Information and Modeling
|
December 14, 2021
Active Site Sequence Representations of Human Kinases Outperform Full Sequence Representations for Affinity Prediction and Inhibitor Generation: 3D Effects in a 1D Model
Jannis Born, Tien Huynh, Astrid Stroobants, et al.
Nucleic Acids Research
|
May 14, 2020
PaccMann: a web service for interpretable anticancer compound sensitivity prediction
Joris Cadow, Jannis Born, Matteo Manica, et al.
Bioinformatics (Oxford, England)
|
July 12, 2021
On the feasibility of deep learning applications using raw mass spectrometry data
Joris Cadow, Matteo Manica, Roland Mathis, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics
|
September 9, 2019
FPGA Accelerated Analysis of Boolean Gene Regulatory Networks
Matteo Manica, Raphael Polig, Mitra Purandare, et al.
Iscience
|
April 14, 2021
PaccMann<sup>RL</sup>: De novo generation of hit-like anticancer molecules from transcriptomic data via reinforcement learning
Jannis Born, Matteo Manica, Ali Oskooei, et al.
Molecular Pharmaceutics
|
October 17, 2019
Toward Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-Based Convolutional Encoders
Matteo Manica, Ali Oskooei, Jannis Born, et al.
Page
of 3
Search research articles
Search
Showing results (1-10 of 24) with videos related to
Sort By:
Page
of 3
Current Medicinal Chemistry
|
July 30, 2021
Trends in Deep Learning for Property-driven Drug Design
Jannis Born, Matteo Manica
Scientific Reports
|
November 6, 2019
Network-based Biased Tree Ensembles (NetBiTE) for Drug Sensitivity Prediction and Drug Sensitivity Biomarker Identification in Cancer
Ali Oskooei, Matteo Manica, Roland Mathis, et al.
NPJ Systems Biology and Applications
|
March 12, 2019
PIMKL: Pathway-Induced Multiple Kernel Learning
Matteo 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 Models
Gianmarco Gabrieli, Matteo Manica, Joris Cadow-Gossweiler, et al.
Journal of Chemical Information and Modeling
|
December 14, 2021
Active Site Sequence Representations of Human Kinases Outperform Full Sequence Representations for Affinity Prediction and Inhibitor Generation: 3D Effects in a 1D Model
Jannis Born, Tien Huynh, Astrid Stroobants, et al.
Nucleic Acids Research
|
May 14, 2020
PaccMann: a web service for interpretable anticancer compound sensitivity prediction
Joris Cadow, Jannis Born, Matteo Manica, et al.
Bioinformatics (Oxford, England)
|
July 12, 2021
On the feasibility of deep learning applications using raw mass spectrometry data
Joris Cadow, Matteo Manica, Roland Mathis, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics
|
September 9, 2019
FPGA Accelerated Analysis of Boolean Gene Regulatory Networks
Matteo Manica, Raphael Polig, Mitra Purandare, et al.
Iscience
|
April 14, 2021
PaccMann<sup>RL</sup>: De novo generation of hit-like anticancer molecules from transcriptomic data via reinforcement learning
Jannis Born, Matteo Manica, Ali Oskooei, et al.
Molecular Pharmaceutics
|
October 17, 2019
Toward Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-Based Convolutional Encoders
Matteo Manica, Ali Oskooei, Jannis Born, et al.
Page
of 3