Konrad Hinsen RSS Feed
https://figshare.com/authors/Konrad_Hinsen/403257
RSS feed for Figshare Profile Konrad HinsenThe Hierarchical Data Format (HDF): A Foundation for Sustainable Data and Software
https://figshare.com/articles/journal_contribution/The_Hierarchical_Data_Format_HDF_A_Foundation_for_Sustainable_Data_and_Software/1112485
When combined with community specific conventions and application-specific semantics, the Hierarchical Data Format (HDF) provides a robust and reliable foundation that many scientific communities rely on for interoperability and high-performance storage of metadata and data. This foundation addresses many technical obstacles related to sustainable data and software, critical steps towards sustainable science. Building on successes across the communities that are using, or could use, HDF5 successfully, requires significant community engagement and development efforts that are outside of the scope of traditional software development projects in research and non-profit organizations like The HDF Group. Identifying individuals and organizations that are already doing the right things and bringing them together to share best practices for funding and executing these activities is an important step towards our shared goal of sustainable science.Computer Software, Data Format, Information Systems2014-09-29 22:02:19Algorithmic models for the natural sciences
https://figshare.com/articles/poster/Algorithmic_models_for_the_natural_sciences_/1046640
Poster presented at the French conference "Journées Nationales GDR GPL 2014" in Paris.Software Engineering, Applied Computer Science, Computational Physics, Computational Biology, Computational Chemistry2014-06-05 10:49:19Mosaic specification 1.0
https://figshare.com/articles/journal_contribution/Mosaic_specification_1_0/879660
MOSAIC: The MOlecular SimulAtion Interchange Conventions
Mosaic is a data model with associated file formats for use with molecular simulation software. This document describes version 1.0 of the data model.Computational Biology, Cheminformatics, Computational Chemistry2013-12-17 13:35:05Model-free simulation approach to molecular diffusion tensors: Water
https://figshare.com/articles/dataset/Model_free_simulation_approach_to_molecular_diffusion_tensors_Water/808595
This file contains part 2 (water) of the supplementary material for the following publication:
Title: Model-free simulation approach to molecular diffusion tensorsAuthors: Guillaume Chevrot, Konrad Hinsen, Gerald R. KnellerJournal: Journal of Chemical Physics 139, 154110 (2013)
It contains the software implementing the computations described in the article, the input datasets for water, the resulting output datasets, and the figures. A detailed list is given below.
The file water_diffusion.ap is a HDF5 file that can be read with any HDF5-compatible software, including the free HDFView package (http://www.hdfgroup.org/hdf-java-html/hdfview/). HDFView can be used to inspect the arrays and tables contained in this file. Reading the molecular structure for water requires software that understands the Mosaic data model (http://bitbucket.org/molsim/mosaic/).
The file has been prepared using the ActivePapers framework (http://bitbucket.org/khinsen/active_papers_py) for reproducible research. It contains all the software used in the study that is described in the article, as well as most of the data, starting from the rigid-body trajectories. The original all-atom Molecular Dynamics trajectories are not included because of their size. All software is written in the Python language. The ActivePapers framework keeps track of which data was generated using which script and also notes the user name, machine name, and versions of all software packages used when running each script.
Readers wishing to modify and re-run the scripts, or to run them on different input data, should download and install the ActivePapers framework.
Datasets contained in the file water_diffusion.ap
The input data to the computations in this file are rigid-body trajectories for each of the 511 water molecules in the original MD trajectory. This input data is too big to be provided here. The correlation functions and mean-square displacements are first computed individually for each water atom and then averaged. The single-molecule functions are also too big to be provided here, except for a subset of five water molecules for demonstration.
All single-molecule data has a numerical suffix. In the following list, only the first one ("_0") is shown.
1) Input data.
1.1) The reference structure of water, with the atomic masses, in Mosaic format.
/data/reference_structures atom_masses configuration universe
1.2) The rigid-body trajectory, consisting of the time axis, the center-of-mass positions, and the orientation stored as a quaternion trajectory.
/data/center_of_mass /data/orientation /data/time
These data sets are links to a separate file which is *not* provided because of its size (16 GB).
2) Correlation functions, mean-square displacements, and trajectory statistice (calclet "correlation_functions")
2.1) Means and variances of the linear and angular velocities. Ideally, the means should be zero and the variances equal to their thermal equilibrium values.
/data/trajectory_statistics mean_angular_velocity_laboratory_frame mean_angular_velocity_molecular_frame mean_velocity_laboratory_frame mean_velocity_molecular_frame variance_angular_velocity_laboratory_frame variance_angular_velocity_molecular_frame variance_velocity_laboratory_frame variance_velocity_molecular_frame
2.2) Correlation functions and mean-square displacements.
The time axes, which are the same for all correlation functions and for all mean-square displacements.
/data/correlation_function_time /data/mean_square_displacement_time
The functions averaged over all 511 water molecules.
/data/averaged correlation_function_laboratory_frame correlation_function_molecular_frame mean_square_displacement_laboratory_frame mean_square_displacement_molecular_frame
The single-molecule functions for the first five molecules.
/data/single_molecule correlation_function_laboratory_frame correlation_function_molecular_frame mean_square_displacement_laboratory_frame mean_square_displacement_molecular_frame
3) Manually set parameters used in computing the diffusion tensors and in prepapring the plots.
correlation_function_integration_limit msd_fit_range msd_plot_range
4) Diffusion tensors from the Kubo relations (integral over the velocity correlation functions) and from the slope of the mean-square displacement.
4.1) The diffusion tensors computed from the data averaged over all molecules.
/data/averaged diffusion_tensor_kubo_laboratory_frame diffusion_tensor_kubo_molecular_frame diffusion_tensor_msd_laboratory_frame diffusion_tensor_msd_molecular_frame
4.2) The diffusion tensors computed from single-molecule data for five molecules.
/data/single_molecule/molecule_0 diffusion_tensor_kubo_laboratory_frame diffusion_tensor_kubo_molecular_frame diffusion_tensor_msd_laboratory_frame diffusion_tensor_msd_molecular_frame
4.3) The variance of the diffusion tensor elements, computed over the five molecules but relative to the average over all 511 molecules.
/data/single_molecule diffusion_tensor_variance_kubo_laboratory_frame diffusion_tensor_variance_kubo_molecular_frame diffusion_tensor_variance_msd_laboratory_frame diffusion_tensor_variance_msd_molecular_frame
4.4) The relative statistical error of the diffusion tensor elements, computed from the variances.
/data/single_molecule diffusion_tensor_relative_error_kubo_laboratory_frame diffusion_tensor_relative_error_kubo_molecular_frame diffusion_tensor_relative_error_msd_laboratory_frame diffusion_tensor_relative_error_msd_molecular_frame
Computational Physics, Condensed Matter Physics2013-09-26 14:59:39Model-free simulation approach to molecular diffusion tensors: Lysozyme
https://figshare.com/articles/dataset/Model_free_simulation_approach_to_molecular_diffusion_tensors_Lysozyme/808594
This file contains part 1 (lysozyme) of the supplementary material for the following publication:
Title: Model-free simulation approach to molecular diffusion tensorsAuthors: Guillaume Chevrot, Konrad Hinsen, Gerald R. KnellerJournal: Journal of Chemical Physics 139, 154110 (2013)
It contains the software implementing the computations described in the article, the input datasets for lysozyme, the resulting output datasets, and the figures. A detailed list is given below.
The file lysozyme_diffusion.ap is a HDF5 file that can be read with any HDF5-compatible software, including the free HDFView package (http://www.hdfgroup.org/hdf-java-html/hdfview/). HDFView can be used to inspect the arrays and tables contained in this file. Reading the protein structure requires software that understands the Mosaic data model (http://bitbucket.org/molsim/mosaic/).
The file has been prepared using the ActivePapers framework (http://bitbucket.org/khinsen/active_papers_py) for reproducible research. It contains all the software used in the study that is described in the article, as well as most of the data, starting from the rigid-body trajectories. The original all-atom Molecular Dynamics trajectories are not included because of their size. All software is written in the Python language. The ActivePapers framework keeps track of which data was generated using which script and also notes the user name, machine name, and versions of all software packages used when running each script.
Readers wishing to modify and re-run the scripts, or to run them on different input data, should download and install the ActivePapers framework.
In order to reduce the file size, some intermediate data (the coordinate and velocity trajectories computed from the original rigid-body trajectories) has been removed from lysozyme_diffusion.ap. It can be restored using the ActivePapers command-line tool using the command
aptool update
Datasets contained in the file lysozyme_diffusion.ap
The computations are based on multiple independent simulations of lysozyme in water. The correlation functions are calculated for each simulation and are then averaged. The diffusion tensor is calculated from the averaged correlation functions. The correlation function plots are presented only for the averages.
All single-trajectory data has a numerical suffix. In the following list, only the first one ("_1") is shown.
1) Input data.
1.1) The reference structure of lysozyme, with the atomic masses, in Mosaic format.
reference_structures reference_structure_1 atom_masses configuration universe
1.2) The rigid-body trajectory, consisting of the time axis, the center-of-mass positions, and the orientation stored as a quaternion trajectory.
trajectory center_of_mass_1 orientation_1 time
1.3) The temperature of the simulation.
temperature
2) Preliminary analyses (calclet thermal_averages).
2.1) The reduced mass of lysozyme in its solvent box,and the tensor of inertia, needed for step 2.2.
mass_and_inertia: reduced_mass_1 inertia_tensor_1
2.2) The theoretical variances of the x, y, z components of the linear and angular velocities in thermal equilibrium. For comparison with the variances computed later from the trajectory.
thermal_velocities variance_angular_velocity_laboratory_frame variance_angular_velocity_molecular_frame variance_velocity_laboratory_frame variance_velocity_molecular_frame
3) Preprocessing of the trajectory (calclet trajectory_processing). This computes the center-of-mass velocities and the angular velocities in the laboratory and molecular frames.
3.1) Means and variances of the linear and angular velocities. Ideally, the means should be zero and the variances equal to the values under "thermal_velocities".
trajectory_statistics mean_angular_velocity_laboratory_frame_1 mean_angular_velocity_molecular_frame_1 mean_velocity_laboratory_frame_1 mean_velocity_molecular_frame_1 variance_angular_velocity_laboratory_frame_1 variance_angular_velocity_molecular_frame_1 variance_velocity_laboratory_frame_1 variance_velocity_molecular_frame_1
3.2) Linear and angular velocities.
velocity_trajectories rotation_laboratory_frame rotation_molecular_frame translation_laboratory_frame translation_molecular_frame
3.3) Linear and angular positions.
coordinate_trajectories rotation_laboratory_frame_1 rotation_molecular_frame_1 translation_laboratory_frame_1 translation_molecular_frame_1
4) Correlation functions and mean-square displacements (calclet correlation_functions).
correlation_functions correlation_function_laboratory_frame_1 correlation_function_molecular_frame_1 correlation_function_laboratory_frame_averaged correlation_function_molecular_frame_averaged correlation_function_time mean_square_displacement_laboratory_frame_1 mean_square_displacement_molecular_frame_1 mean_square_displacement_laboratory_frame_averaged mean_square_displacement_molecular_frame_averaged mean_square_displacement_time
5) Manually set parameters used in computing the diffusion tensors.
correlation_function_integration_limit correlation_function_plot_range msd_fit_range msd_plot_range
6) Diffusion tensors from the Kubo relations (integral over the velocity correlation functions) and from the slope of the mean-square displacement.
diffusion_tensor_kubo_laboratory_frame diffusion_tensor_kubo_molecular_frame diffusion_tensor_msd_laboratory_frame diffusion_tensor_msd_molecular_frame
Biophysics, Computational Physics, Condensed Matter Physics2013-09-26 14:50:07A comparison of reduced coordinate sets for describing protein structure
https://figshare.com/articles/dataset/A_comparison_of_reduced_coordinate_sets_for_describing_protein_structure/798825
This file contains supplementary material for the following publication:
Title: A comparison of reduced coordinate sets for describing protein structureAuthors: Konrad Hinsen, Shuangwei Hu, Gerald R. Kneller, Antti J. NiemiJournal: Journal of Chemical Physics 139, 124115 (2013)
DOI: 10.1063/1.4821598
It contains the software implementing the computations described in the article, the input dataset, the output datasets, and the figures. A detailed list is given below.
Instructions for use
The file software_and_datasets.ap is an HDF5 file that can be read with any HDF5-compatible software, including the free HDFView package (http://www.hdfgroup.org/hdf-java-html/hdfview/). HDFView can be used to inspect the tables contained in this file. Reading the protein structures requires software that understands the Mosaic data model (http://bitbucket.org/molsim/mosaic/).
The file software_and_datasets.ap has been prepared using the ActivePapers framework (http://bitbucket.org/khinsen/active_papers_py) for reproducible research. It contains all the software used in the study that is described in the article, from the download of the protein structures to the generation of the figures. All software is written in the Python language. The ActivePapers framework keeps track of which data was generated using which script and also notes the user name, machine name, and versions of all software packages used when running each script.
Readers wishing to modify and re-run the scripts, or to run the on different input data, should download and install the ActivePapers framework.
Datasets contained in the ActivePaper file
/data/pdb_structures
The orginal protein structures imported from the PDB. Only the backbone atoms relevant for our study (N, CA, C) are stored. There is one subgroup for each PDB code, and each subgroup contains a Mosaic universe and a Mosaic configuration.
For more information about Mosaic, see https://bitbucket.org/molsim/mosaic/.
/data/coordinate_analysis/ averages variances histograms
The distributions of the internal coordinates of the backbone, computed over all residues of all protein structures. For each coordinate, there is an average value and a variance, and a histogram of the values.
/data/reconstructions
The protein backbone configurations reconstructed from various reduced coordinate sets.
/data/number_of_residues/data/root_mean_square_distances/data/radii_of_gyration
Tables containing for each protein the number of residues, the root-mean-square distances from each reconstruction to the initial structure, and the radii of gyration for the initial structure and all reconstructions.
/data/rg_analysis
The fits of the asymptotic large-N behavior of the radii of gyration for the initial configurations and all reconstructions.
/documentation/ 2OVU_initial.pdb 2OVU_ca.pdb 2OVU_phipsi.pdb
The PDB files for the initial configuration, the reconstruction from virtual-CA coordinates, and the reconstruction from phi-psi coordinates.
/documentation/ histograms_distance.pdf histograms_angle.pdf histograms_dihedral.pdf
The histograms of the internal coordinate values.
/documentation/rmsd.pdf
The plot of the RMSD distances between the reconstructions and the initial configurations.
/documentation/rg.pdf
The plots of the radii of gyration for each reconstruction, with the asymptotic fits.
Computational Biology2013-09-13 09:43:44pyMosaic 0.1.1 in ActivePapers format
https://figshare.com/articles/software/pyMosaic_0_1_1_in_ActivePapers_format/705829
This file is obsolete. A new version, pyMosaic 0.2.0, is available at http://dx.doi.org/10.5281/zenodo.7648
This ActivePaper contains the pyMosaic library packaged and published to make it available for use in other ActivePaper documents.
Mosaic is a modular data model for molecular simulation applications. The Mosaic Python library provides an in-memory representation of Mosaic data items plus input/output in HDF5 and XML formats.
This ActivePaper contains only the Mosaic Python library and the documentation. The full Mosaic distribution also contains a library for importing from the Protein Data Bank (PDB) and a command-line tool for file conversion. These parts make no sense in the ActivePapers framework and are therefore not contained in this distribution.
ActivePapers is a computational science framework that supports reproducible research and publishing computations. An ActivePaper can contain any combination of code, data, and documentation. The pyMosaic ActivePaper is a code library with documentation. It can be referenced by other ActivePapers that contain molecular simulation data in Mosaic HDF5 format.Computational Physics, Computational Biology, Cheminformatics2013-05-22 07:08:30ImmutablePy 0.1 in ActivePapers format
https://figshare.com/articles/software/ImmutablePy_0_1_in_ActivePapers_format/692144
This ActivePaper contains the ImmutablePy library packaged and published to make it available for use in other ActivePaper documents.Applied Computer Science2013-04-26 12:37:48