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421 to 430 of 454 Results

Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models Dec 18, 2020 - Metabolic Networks Johann F. Jadebeck; Axel Theorell; Samuel Leweke; Katharina Nöh, 2020, "Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models", https://doi.org/10.26165/JUELICH-DATA/YXLFKJ, Jülich DATA, V1 This collection contains showcased models and pre-processing results (determining an independent flux space and rounding) that are used as basis for benchmarking the uniform sampling performance of the CHHR implementations of the HOPS library [10.1093/bioinformatics/btaa872] (htt...
Metabolic Networks Dec 18, 2020Institute of Bio- and Geosciences – Biotechnology (IBG-1) This dataverse contains models and data related to metabolic networks and fluxomics.
Institute of Bio- and Geosciences – Biotechnology (IBG-1)(Forschungszentrum Jülich) Dec 18, 2020 The dataverse of the Institute of Bio- and Geosciences – Biotechnology (IBG-1)
Data for: Flux periodic oscillations and phase-coherent transport in GeTe nanowire-based devices Dec 16, 2020 - Peter Grünberg Institute – Semiconductor Nanoelectronics (PGI-9) Zhang, Jinzhong; Tse, Pok-Lam; Jalil, Abdur-Rehman; Kölzer, Jonas; Rosenbach, Daniel; Luysberg, Martina; Panaitov, Gergory; Lüth, Hans; Hu, Zhigao; Grützmacher, Detlev; Lüth, Hans; Lu, Jia Grace; Schäpers, Thomas, 2020, "Data for: Flux periodic oscillations and phase-coherent transport in GeTe nanowire-based devices", https://doi.org/10.26165/JUELICH-DATA/M1IQVG, Jülich DATA, V1 Flux periodic oscillations and phase-coherent transport in GeTe nanowire-based devices: Source data underlying Figs. 1-4 and Supplementary Figs. S3, S6, and S8.
Peter Grünberg Institute – Semiconductor Nanoelectronics (PGI-9)(Forschungszentrum Jülich ) Dec 16, 2020 The dataverse of the Peter Grünberg Institute – Semiconductor Nanoelectronics (PGI-9)
Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects Dec 9, 2020 - Computational Neurology Dataverse Rosjat, Nils; Wang, Bin A.; Liu, Liqing; Fink, Gereon R.; Daun, Silvia, 2020, "Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects", https://doi.org/10.26165/JUELICH-DATA/T1PKNZ, Jülich DATA, V1 Data description This dataset includes EEG recordings of 18 younger healthy subjects (18-35yrs) and 24 older healthy subjects (60+yrs) while they performed a visually cued finger tapping task. The task includes a visually-cued index finger tapping task and a vision-only control c...
Heinz Maier-Leibnitz Zentrum (MLZ) Nov 24, 2020Jülich Centre for Neutron Science (JCNS)
Jülich Centre for Neutron Science (JCNS)(Forschungszentrum Jülich) Nov 24, 2020 The dataverse of the Jülich Centre for Neutron Science (JCNS)
Dynamics of Complex Fluids and Interfaces(Forschungszentrum Jülich) Nov 23, 2020Institute of Energy and Climate Research – Helmholtz Institute Erlangen-Nürnberg for Renewable Energy (IEK-11) Research data of the Dept. Dynamics of Complex Fluids and Interfaces at HI ERN (IEK-11)
Replication Data for: Trajectory Data Set from the study on the 2017 BC wildfire detection Nov 20, 2020 - CLaMS Dataverse Grooß, Jens-Uwe, 2020, "Replication Data for: Trajectory Data Set from the study on the 2017 BC wildfire detection", https://doi.org/10.26165/JUELICH-DATA/ATC1MZ, Jülich DATA, V1 These are trajectory data calculated for the study by Hooghiem et al. (Atmos Chem. Phys. , 2020). In this study, wildfire-influenced airmasses were observed and the trajectories were used to trace back the origin.

Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models

Dec 18, 2020 - Metabolic Networks

Johann F. Jadebeck; Axel Theorell; Samuel Leweke; Katharina Nöh, 2020, "Replication Data for: HOPS: high-performance library for (non-)uniform sampling of convex-constrained models", https://doi.org/10.26165/JUELICH-DATA/YXLFKJ, Jülich DATA, V1

This collection contains showcased models and pre-processing results (determining an independent flux space and rounding) that are used as basis for benchmarking the uniform sampling performance of the CHHR implementations of the HOPS library [10.1093/bioinformatics/btaa872] (htt...

Metabolic Networks

Dec 18, 2020Institute of Bio- and Geosciences – Biotechnology (IBG-1)

This dataverse contains models and data related to metabolic networks and fluxomics.

Institute of Bio- and Geosciences – Biotechnology (IBG-1)(Forschungszentrum Jülich)

Dec 18, 2020

The dataverse of the Institute of Bio- and Geosciences – Biotechnology (IBG-1)

Data for: Flux periodic oscillations and phase-coherent transport in GeTe nanowire-based devices

Dec 16, 2020 - Peter Grünberg Institute – Semiconductor Nanoelectronics (PGI-9)

Zhang, Jinzhong; Tse, Pok-Lam; Jalil, Abdur-Rehman; Kölzer, Jonas; Rosenbach, Daniel; Luysberg, Martina; Panaitov, Gergory; Lüth, Hans; Hu, Zhigao; Grützmacher, Detlev; Lüth, Hans; Lu, Jia Grace; Schäpers, Thomas, 2020, "Data for: Flux periodic oscillations and phase-coherent transport in GeTe nanowire-based devices", https://doi.org/10.26165/JUELICH-DATA/M1IQVG, Jülich DATA, V1

Flux periodic oscillations and phase-coherent transport in GeTe nanowire-based devices: Source data underlying Figs. 1-4 and Supplementary Figs. S3, S6, and S8.

Peter Grünberg Institute – Semiconductor Nanoelectronics (PGI-9)(Forschungszentrum Jülich )

Dec 16, 2020

The dataverse of the Peter Grünberg Institute – Semiconductor Nanoelectronics (PGI-9)

Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects

Dec 9, 2020 - Computational Neurology Dataverse

Rosjat, Nils; Wang, Bin A.; Liu, Liqing; Fink, Gereon R.; Daun, Silvia, 2020, "Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects", https://doi.org/10.26165/JUELICH-DATA/T1PKNZ, Jülich DATA, V1

Data description This dataset includes EEG recordings of 18 younger healthy subjects (18-35yrs) and 24 older healthy subjects (60+yrs) while they performed a visually cued finger tapping task. The task includes a visually-cued index finger tapping task and a vision-only control c...

Heinz Maier-Leibnitz Zentrum (MLZ)

Nov 24, 2020Jülich Centre for Neutron Science (JCNS)

Jülich Centre for Neutron Science (JCNS)(Forschungszentrum Jülich)

Nov 24, 2020

The dataverse of the Jülich Centre for Neutron Science (JCNS)

Dynamics of Complex Fluids and Interfaces(Forschungszentrum Jülich)

Nov 23, 2020Institute of Energy and Climate Research – Helmholtz Institute Erlangen-Nürnberg for Renewable Energy (IEK-11)

Research data of the Dept. Dynamics of Complex Fluids and Interfaces at HI ERN (IEK-11)

Replication Data for: Trajectory Data Set from the study on the 2017 BC wildfire detection

Nov 20, 2020 - CLaMS Dataverse

Grooß, Jens-Uwe, 2020, "Replication Data for: Trajectory Data Set from the study on the 2017 BC wildfire detection", https://doi.org/10.26165/JUELICH-DATA/ATC1MZ, Jülich DATA, V1

These are trajectory data calculated for the study by Hooghiem et al. (Atmos Chem. Phys. , 2020). In this study, wildfire-influenced airmasses were observed and the trajectories were used to trace back the origin.

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