EXC 2075 Project Networks

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Deposit Date: 2021

1 to 10 of 18 Results

Supplementary material for 'Exploring the Effect of Enhanced Sampling on Protein Stability Prediction' May 4, 2022 - Institute of Thermodynamics and Thermal Process Engineering Fleck, Maximilian; Markthaler, Daniel; Stankiewicz, Bartosz; Hansen, Niels, 2022, "Supplementary material for 'Exploring the Effect of Enhanced Sampling on Protein Stability Prediction'", https://doi.org/10.18419/darus-2132, DaRUS, V1, UNF:6:8wyFNcxoOTcKA+4ZpSWLAg== [fileUNF] Supplementary material for 'Exploring the Effect of Enhanced Sampling on Protein Stability Prediction' containing files to (re-)execute GROMACS simulations performed during the mutation study. This dataset contains simulation input files in GROMACS format accompanying the mention...
Supplementary material for 'Influence of Layer Slipping on Adsorption of Light Gases in Covalent Organic Frameworks: A Combined Experimental and Computational Study' Apr 26, 2022 - Institute of Thermodynamics and Thermal Process Engineering Kessler, Christopher; Schuldt, Robin; Emmerling, Sebastian; Lotsch, Bettina; Kästner, Johannes; Gross, Joachim; Hansen, Niels, 2022, "Supplementary material for 'Influence of Layer Slipping on Adsorption of Light Gases in Covalent Organic Frameworks: A Combined Experimental and Computational Study'", https://doi.org/10.18419/darus-2308, DaRUS, V1, UNF:6:ifmtNZEZHi+MkSvB5rd1dw== [fileUNF] This dataset contains results from Grand Canonical Monte Carlo (GCMC) Simulation (data/isotherms_sim/) and experiment (data/isotherms/exp). All Data is presented in a jupyter notebook and for a fast overview without executing the notebook also as pdf-file. Furthermore the dataset...
Replication Data for: Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework Mar 29, 2022 - PN 6 Holzmüller, David, 2022, "Replication Data for: Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework", https://doi.org/10.18419/darus-1779, DaRUS, V1, UNF:6:aIyuHfDcWPT9LJvtkCge9w== [fileUNF] This dataset contains supplementary code for the paper Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework. The code is also provided on GitHub. Here, we additionally provide the runtime measurement data generated by the code, which...
NMTVis - Extended Neural Machine Translation Visualization System Jan 26, 2022 - PN 6-4 Munz, Tanja; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel, 2022, "NMTVis - Extended Neural Machine Translation Visualization System", https://doi.org/10.18419/darus-2124, DaRUS, V1 NMTVis is a web-based visual analytics system to analyze, understand, and correct translations generated with neural machine translation. First, a document can be translated using a neural machine translation model (we support an LSTM-based and the Transformer architecture). Afte...
PyPlant: A Python Framework for Cached Function Pipelines Jan 24, 2022 - PN 6-6 Tkachev, Gleb, 2022, "PyPlant: A Python Framework for Cached Function Pipelines", https://doi.org/10.18419/darus-2249, DaRUS, V1 PyPlant is a simple coroutine-based framework for writing data processing pipelines. PyPlant's goal is to simplify caching of intermediate results in the pipeline and avoid re-running expensive early stages of the pipeline, when only the later stages have changed.
Supplementary material for 'Binding free energies for the SAMPL8 CB8 "Drugs of Abuse" challenge from umbrella sampling combined with Hamiltonian replica exchange' Jan 16, 2022 - Institute of Thermodynamics and Thermal Process Engineering Markthaler, Daniel; Kraus, Hamzeh; Hansen, Niels, 2022, "Supplementary material for 'Binding free energies for the SAMPL8 CB8 "Drugs of Abuse" challenge from umbrella sampling combined with Hamiltonian replica exchange'", https://doi.org/10.18419/darus-2109, DaRUS, V1 Binding affinities of seven drug molecules (G1-G7) towards a common receptor (cucurbit[8]uril, CB8) were estimated from molecular dynamics (MD) simulations in the scope of the recent SAMPL8 CB8 "Drugs of Abuse" challenge using the GROMACS MD package. To compare with experimental...
Supplementary material for 'Umbrella sampling and double decoupling data for methanol binding to Candida antarctica lipase B' Nov 25, 2021 - Molecular Simulation Markthaler, Daniel; Hansen, Niels, 2021, "Supplementary material for 'Umbrella sampling and double decoupling data for methanol binding to Candida antarctica lipase B'", https://doi.org/10.18419/darus-2104, DaRUS, V1 This dataset contains all relevant simulation input files (topologies, coordinates, simulation parameters), generated simulation output (final configurations, time series of collective variables) together with scripts used for set-up and analysis of the umbrella sampling and doub...
Code for relative permeabilities for two-phase flow between parallel plates with slip conditions Nov 24, 2021 - PN 1-6 Schulz, Sebastian; Bringedal, Carina; Ackermann, Sina, 2021, "Code for relative permeabilities for two-phase flow between parallel plates with slip conditions", https://doi.org/10.18419/darus-2241, DaRUS, V1 This MATLAB code calculates relative permeabilities of two fluids flowing between two parallel plates, depending on their viscosities, saturation and boundary conditions at the top and bottom plates. The underlying assumptions behind the derivation are shown in the pdf "overview_...
Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments Oct 15, 2021 - PN 6 Zaverkin, Viktor; Holzmüller, David; Steinwart, Ingo; Kästner, Johannes, 2021, "Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments", https://doi.org/10.18419/darus-2136, DaRUS, V1 Code and documentation for the improved Gaussian Moments Neural Network (GM-NN). An updated version can be found on GitLab
Replication Data for: "S4: Self-Supervised learning of Spatiotemporal Similarity" Oct 5, 2021 - PN 6-6 Tkachev, Gleb, 2021, "Replication Data for: "S4: Self-Supervised learning of Spatiotemporal Similarity"", https://doi.org/10.18419/darus-2174, DaRUS, V1 We train a self-supervised siamese model that enables querying for similar behavior on spatiotemporal volumes. Here we provide the code and data needed to reproduce the representative figures of the paper. See the notes and the included readme file for details.

Supplementary material for 'Exploring the Effect of Enhanced Sampling on Protein Stability Prediction'

May 4, 2022 - Institute of Thermodynamics and Thermal Process Engineering

Fleck, Maximilian; Markthaler, Daniel; Stankiewicz, Bartosz; Hansen, Niels, 2022, "Supplementary material for 'Exploring the Effect of Enhanced Sampling on Protein Stability Prediction'", https://doi.org/10.18419/darus-2132, DaRUS, V1, UNF:6:8wyFNcxoOTcKA+4ZpSWLAg== [fileUNF]

Supplementary material for 'Exploring the Effect of Enhanced Sampling on Protein Stability Prediction' containing files to (re-)execute GROMACS simulations performed during the mutation study. This dataset contains simulation input files in GROMACS format accompanying the mention...

Supplementary material for 'Influence of Layer Slipping on Adsorption of Light Gases in Covalent Organic Frameworks: A Combined Experimental and Computational Study'

Apr 26, 2022 - Institute of Thermodynamics and Thermal Process Engineering

Kessler, Christopher; Schuldt, Robin; Emmerling, Sebastian; Lotsch, Bettina; Kästner, Johannes; Gross, Joachim; Hansen, Niels, 2022, "Supplementary material for 'Influence of Layer Slipping on Adsorption of Light Gases in Covalent Organic Frameworks: A Combined Experimental and Computational Study'", https://doi.org/10.18419/darus-2308, DaRUS, V1, UNF:6:ifmtNZEZHi+MkSvB5rd1dw== [fileUNF]

This dataset contains results from Grand Canonical Monte Carlo (GCMC) Simulation (data/isotherms_sim/) and experiment (data/isotherms/exp). All Data is presented in a jupyter notebook and for a fast overview without executing the notebook also as pdf-file. Furthermore the dataset...

Replication Data for: Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework

Mar 29, 2022 - PN 6

Holzmüller, David, 2022, "Replication Data for: Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework", https://doi.org/10.18419/darus-1779, DaRUS, V1, UNF:6:aIyuHfDcWPT9LJvtkCge9w== [fileUNF]

This dataset contains supplementary code for the paper Fast Sparse Grid Operations using the Unidirectional Principle: A Generalized and Unified Framework. The code is also provided on GitHub. Here, we additionally provide the runtime measurement data generated by the code, which...

NMTVis - Extended Neural Machine Translation Visualization System

Jan 26, 2022 - PN 6-4

Munz, Tanja; Väth, Dirk; Kuznecov, Paul; Vu, Ngoc Thang; Weiskopf, Daniel, 2022, "NMTVis - Extended Neural Machine Translation Visualization System", https://doi.org/10.18419/darus-2124, DaRUS, V1

NMTVis is a web-based visual analytics system to analyze, understand, and correct translations generated with neural machine translation. First, a document can be translated using a neural machine translation model (we support an LSTM-based and the Transformer architecture). Afte...

PyPlant: A Python Framework for Cached Function Pipelines

Jan 24, 2022 - PN 6-6

Tkachev, Gleb, 2022, "PyPlant: A Python Framework for Cached Function Pipelines", https://doi.org/10.18419/darus-2249, DaRUS, V1

PyPlant is a simple coroutine-based framework for writing data processing pipelines. PyPlant's goal is to simplify caching of intermediate results in the pipeline and avoid re-running expensive early stages of the pipeline, when only the later stages have changed.

Supplementary material for 'Binding free energies for the SAMPL8 CB8 "Drugs of Abuse" challenge from umbrella sampling combined with Hamiltonian replica exchange'

Jan 16, 2022 - Institute of Thermodynamics and Thermal Process Engineering

Markthaler, Daniel; Kraus, Hamzeh; Hansen, Niels, 2022, "Supplementary material for 'Binding free energies for the SAMPL8 CB8 "Drugs of Abuse" challenge from umbrella sampling combined with Hamiltonian replica exchange'", https://doi.org/10.18419/darus-2109, DaRUS, V1

Binding affinities of seven drug molecules (G1-G7) towards a common receptor (cucurbit[8]uril, CB8) were estimated from molecular dynamics (MD) simulations in the scope of the recent SAMPL8 CB8 "Drugs of Abuse" challenge using the GROMACS MD package. To compare with experimental...

Supplementary material for 'Umbrella sampling and double decoupling data for methanol binding to Candida antarctica lipase B'

Nov 25, 2021 - Molecular Simulation

Markthaler, Daniel; Hansen, Niels, 2021, "Supplementary material for 'Umbrella sampling and double decoupling data for methanol binding to Candida antarctica lipase B'", https://doi.org/10.18419/darus-2104, DaRUS, V1

This dataset contains all relevant simulation input files (topologies, coordinates, simulation parameters), generated simulation output (final configurations, time series of collective variables) together with scripts used for set-up and analysis of the umbrella sampling and doub...

Code for relative permeabilities for two-phase flow between parallel plates with slip conditions

Nov 24, 2021 - PN 1-6

Schulz, Sebastian; Bringedal, Carina; Ackermann, Sina, 2021, "Code for relative permeabilities for two-phase flow between parallel plates with slip conditions", https://doi.org/10.18419/darus-2241, DaRUS, V1

This MATLAB code calculates relative permeabilities of two fluids flowing between two parallel plates, depending on their viscosities, saturation and boundary conditions at the top and bottom plates. The underlying assumptions behind the derivation are shown in the pdf "overview_...

Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments

Oct 15, 2021 - PN 6

Zaverkin, Viktor; Holzmüller, David; Steinwart, Ingo; Kästner, Johannes, 2021, "Code for: Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments", https://doi.org/10.18419/darus-2136, DaRUS, V1

Code and documentation for the improved Gaussian Moments Neural Network (GM-NN). An updated version can be found on GitLab

Replication Data for: "S4: Self-Supervised learning of Spatiotemporal Similarity"

Oct 5, 2021 - PN 6-6

Tkachev, Gleb, 2021, "Replication Data for: "S4: Self-Supervised learning of Spatiotemporal Similarity"", https://doi.org/10.18419/darus-2174, DaRUS, V1

We train a self-supervised siamese model that enables querying for similar behavior on spatiotemporal volumes. Here we provide the code and data needed to reproduce the representative figures of the paper. See the notes and the included readme file for details.

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