Stuttgart Center for Simulation Science (SC SimTech)

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1 to 10 of 337 Results

Data for Tau method Feb 13, 2026 - tBME project Hsueh, Han-Fang, 2026, "Data for Tau method", https://doi.org/10.18419/DARUS-2936, DaRUS, V1 Code and data for the publication "Optimized Predictive Coverage by Averaging Time-Windowed Bayesian Distributions" (2024). The folder "code_tau_method" includes the files and data to generate the plots for cases of a didactic example, one synthetic dataset and one real dataset discussed in the publication. It includes seven 9 *.m files, 2 folders...
Supplementary Data to: "Activation mechanism of the full-length histidine kinase LvrB, a master virulence regulator in pathogenic Leptospira" Feb 10, 2026 - PN 3-11 Pluhackova, Kristyna, 2026, "Supplementary Data to: "Activation mechanism of the full-length histidine kinase LvrB, a master virulence regulator in pathogenic Leptospira"", https://doi.org/10.18419/DARUS-5664, DaRUS, V1 Initial coordinate and simulation input files and a coordinate files of the final outputs as well as of the simulation trajectories (protein only) for all-atom MD simulations of LvrB performed using CHARMM36m/TIP4p in GROMACS2023. (pdb, xtc) Simulation data on phosphorylated aspartic acid (residue APP) with parameters generated by CHARMM-GUI are in...
Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching" Feb 10, 2026 - PN 3-11 Korn, Viktoria Helena; Pluhackova, Kristyna, 2026, "Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"", https://doi.org/10.18419/DARUS-5682, DaRUS, V1 GROMACS simulation files, input and final structures for CHARMM36m MD simulations including our refined parameters for phosphorylated serine in 3 different protonation states. The directory charmm36-jul22mod.ff contains our refined parameters.
Supplementary data to "Roles of ligand, phosphorylation, and membrane in assembling human β2-adrenergic receptor-β-arrestin complexes" Feb 3, 2026 - PN 3-11 Pluhackova, Kristyna, 2026, "Supplementary data to "Roles of ligand, phosphorylation, and membrane in assembling human β2-adrenergic receptor-β-arrestin complexes"", https://doi.org/10.18419/DARUS-5513, DaRUS, V1 GROMACS simulation files, initial and final snapshots (all atoms) as well as simulation trajectories (proteins, ligands, membrane) of (i) beta-arrestin 2 (barr2) in inactive and active form interacting with a membrane with or without PIP2 lipids, (ii) beta2-adrenergic receptor activated by adrenaline and either phosphorylated on S355 and S356 or no...
Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations Jan 14, 2026 - Coarse-grained non-equilibrium dynamics with generative machine learning Egenlauf, Patrick; Březinová, Iva; Andergassen, Sabine; Klopotek, Miriam, 2026, "Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations", https://doi.org/10.18419/DARUS-5613, DaRUS, V1 This dataset contains all relevant data to reproduce the results of the paper titled "Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations". It contains the exact time series data of the two-particle reduced density matrix (2RDM) for each parameter configuration of the parameter scan, with...
Optimization of magnetoelectric composites using convolutional neural networks - scripts and dataset Dec 22, 2025 - PN 3-5 Sriram, Siddharth, 2025, "Optimization of magnetoelectric composites using convolutional neural networks - scripts and dataset", https://doi.org/10.18419/DARUS-5623, DaRUS, V1 This repository is intended to host the supplementary material (dataset and scripts) associated with the article “Optimization of magnetoelectric composites using convolutional neural networks”. The HDF5 file 'Microstructure_data.h5' contains the dataset of microstructural images and their effective properties of interest, computed using the finite...
Coarse-grained non-equilibrium dynamics with generative machine learning(Universität Stuttgart) Dec 15, 2025PN 6
Replication Data for: "BSP k-Means" Dec 11, 2025 - PN 6-4 Künzel, Sebastian; Weiskopf, Daniel, 2025, "Replication Data for: "BSP k-Means"", https://doi.org/10.18419/DARUS-5575, DaRUS, V1 This dataset contains reference implementations in C++ and CUDA for the algorithm presented in the paper "BSP k-Means". The purpose of the data is to allow replication of the reported results.
Kinetic modeling of enzymatic cephalexin synthesis with neural ODEs and surrogate-accelerated Bayesian inference Dec 9, 2025 - PN 2-6 Range, Jan Peter; Pleiss, Jürgen; Bommarius, Andreas, 2025, "Kinetic modeling of enzymatic cephalexin synthesis with neural ODEs and surrogate-accelerated Bayesian inference", https://doi.org/10.18419/DARUS-5539, DaRUS, V1, UNF:6:l47sIu5Gd2e6cn3HDM5h6g== [fileUNF] α-Amino ester hydrolases (AEHs) offer a promising route to the stereoselective synthesis of β-lactams such as cephalexin. However, published kinetic studies have encountered difficulty when extended beyond fitting of the data, indicating practical non-identifiability of the underlying kinetic models. Here, we address this issue using Bayesian infer...
Replication Code for: Augmenting a pure and hybrid vertical equilibrium scheme via data-driven surrogate modelling Dec 1, 2025 - PN 5-2 (II) Buntic, Ivan; Flemisch, Bernd, 2025, "Replication Code for: Augmenting a pure and hybrid vertical equilibrium scheme via data-driven surrogate modelling", https://doi.org/10.18419/DARUS-5343, DaRUS, V2 This data set contains the source code to reproduce the simulation and data-driven models for the publication Augmenting a pure and hybrid vertical me via data-driven surrogate modelling, that has been submitted to the Transport in Porous Media journal. Files README.md: Instructions on installing all necessary modules using git or Docker. install_b...

Data for Tau method

Feb 13, 2026 - tBME project

Hsueh, Han-Fang, 2026, "Data for Tau method", https://doi.org/10.18419/DARUS-2936, DaRUS, V1

Code and data for the publication "Optimized Predictive Coverage by Averaging Time-Windowed Bayesian Distributions" (2024). The folder "code_tau_method" includes the files and data to generate the plots for cases of a didactic example, one synthetic dataset and one real dataset discussed in the publication. It includes seven 9 *.m files, 2 folders...

Supplementary Data to: "Activation mechanism of the full-length histidine kinase LvrB, a master virulence regulator in pathogenic Leptospira"

Feb 10, 2026 - PN 3-11

Pluhackova, Kristyna, 2026, "Supplementary Data to: "Activation mechanism of the full-length histidine kinase LvrB, a master virulence regulator in pathogenic Leptospira"", https://doi.org/10.18419/DARUS-5664, DaRUS, V1

Initial coordinate and simulation input files and a coordinate files of the final outputs as well as of the simulation trajectories (protein only) for all-atom MD simulations of LvrB performed using CHARMM36m/TIP4p in GROMACS2023. (pdb, xtc) Simulation data on phosphorylated aspartic acid (residue APP) with parameters generated by CHARMM-GUI are in...

Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"

Feb 10, 2026 - PN 3-11

Korn, Viktoria Helena; Pluhackova, Kristyna, 2026, "Supplementary Material for "Refinement of CHARMM36m force field parameters for protein phosphorylation by force-matching"", https://doi.org/10.18419/DARUS-5682, DaRUS, V1

GROMACS simulation files, input and final structures for CHARMM36m MD simulations including our refined parameters for phosphorylated serine in 3 different protonation states. The directory charmm36-jul22mod.ff contains our refined parameters.

Supplementary data to "Roles of ligand, phosphorylation, and membrane in assembling human β2-adrenergic receptor-β-arrestin complexes"

Feb 3, 2026 - PN 3-11

Pluhackova, Kristyna, 2026, "Supplementary data to "Roles of ligand, phosphorylation, and membrane in assembling human β2-adrenergic receptor-β-arrestin complexes"", https://doi.org/10.18419/DARUS-5513, DaRUS, V1

GROMACS simulation files, initial and final snapshots (all atoms) as well as simulation trajectories (proteins, ligands, membrane) of (i) beta-arrestin 2 (barr2) in inactive and active form interacting with a membrane with or without PIP2 lipids, (ii) beta2-adrenergic receptor activated by adrenaline and either phosphorylated on S355 and S356 or no...

Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations

Jan 14, 2026 - Coarse-grained non-equilibrium dynamics with generative machine learning

Egenlauf, Patrick; Březinová, Iva; Andergassen, Sabine; Klopotek, Miriam, 2026, "Replication Data for: Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations", https://doi.org/10.18419/DARUS-5613, DaRUS, V1

This dataset contains all relevant data to reproduce the results of the paper titled "Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations". It contains the exact time series data of the two-particle reduced density matrix (2RDM) for each parameter configuration of the parameter scan, with...

Optimization of magnetoelectric composites using convolutional neural networks - scripts and dataset

Dec 22, 2025 - PN 3-5

Sriram, Siddharth, 2025, "Optimization of magnetoelectric composites using convolutional neural networks - scripts and dataset", https://doi.org/10.18419/DARUS-5623, DaRUS, V1

This repository is intended to host the supplementary material (dataset and scripts) associated with the article “Optimization of magnetoelectric composites using convolutional neural networks”. The HDF5 file 'Microstructure_data.h5' contains the dataset of microstructural images and their effective properties of interest, computed using the finite...

Coarse-grained non-equilibrium dynamics with generative machine learning(Universität Stuttgart)

Dec 15, 2025PN 6

Replication Data for: "BSP k-Means"

Dec 11, 2025 - PN 6-4

Künzel, Sebastian; Weiskopf, Daniel, 2025, "Replication Data for: "BSP k-Means"", https://doi.org/10.18419/DARUS-5575, DaRUS, V1

This dataset contains reference implementations in C++ and CUDA for the algorithm presented in the paper "BSP k-Means". The purpose of the data is to allow replication of the reported results.

Kinetic modeling of enzymatic cephalexin synthesis with neural ODEs and surrogate-accelerated Bayesian inference

Dec 9, 2025 - PN 2-6

Range, Jan Peter; Pleiss, Jürgen; Bommarius, Andreas, 2025, "Kinetic modeling of enzymatic cephalexin synthesis with neural ODEs and surrogate-accelerated Bayesian inference", https://doi.org/10.18419/DARUS-5539, DaRUS, V1, UNF:6:l47sIu5Gd2e6cn3HDM5h6g== [fileUNF]

α-Amino ester hydrolases (AEHs) offer a promising route to the stereoselective synthesis of β-lactams such as cephalexin. However, published kinetic studies have encountered difficulty when extended beyond fitting of the data, indicating practical non-identifiability of the underlying kinetic models. Here, we address this issue using Bayesian infer...

Replication Code for: Augmenting a pure and hybrid vertical equilibrium scheme via data-driven surrogate modelling

Dec 1, 2025 - PN 5-2 (II)

Buntic, Ivan; Flemisch, Bernd, 2025, "Replication Code for: Augmenting a pure and hybrid vertical equilibrium scheme via data-driven surrogate modelling", https://doi.org/10.18419/DARUS-5343, DaRUS, V2

This data set contains the source code to reproduce the simulation and data-driven models for the publication Augmenting a pure and hybrid vertical me via data-driven surrogate modelling, that has been submitted to the Transport in Porous Media journal. Files README.md: Instructions on installing all necessary modules using git or Docker. install_b...

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