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16 results for “Crystallographic data”
MD Data for Patterns in protein flexibility: a comparison of NMR "ensembles", MD trajectories and crystallographic B-factors
<p>This data set comprises five zipped directories that contain the scripts and intermediate molecular dynamics (MD) results used in (initially as of April 24, 2017, updated with additional directories on December 15, 2020) a soon to be submitted paper, "Patterns in protein flexibility: a comparison of NMR 'ensembles', MD trajectories and crystallographic B-factors" written by the authors of this entry. An earlier version of this paper is available via BioRxiv, DOI: https://doi.org/10.1101/240655.</p> <p>This paper explores patterns in coordinate variance and coordinate uncertainty in MD trajectories and in protein structures derived from NMR and compares coordinate variances/uncertainties with those crystallographic B-factors. The files, MD_data.zip and MD_data2.zip, each unzip to contain input files and scripts for reproducing the MD trajectories used in this paper (using DESMOND): MD_data.zip contains input files/scripts for the MD trajectories used in the preprint; MD_data2.zip contains input files/scripts for trajectories ran following publication of the preprint. The file btab_analysis_scripts.zip contains key scripts for analyzing those trajectories (following file conversion with VMD and superimposition with THESEUS) in MATLAB (this analysis assumes the presence of the FindCore Toolbox, written by David Snyder and available via the MATLAB Central File Exchange, as well as the MATLAB Statistics and Machine Learning Toolbox). And the files, superimposed_MD_trajectories.zip and superimposed_MD_trajectories2.zip, each unzip to yield the trajectories (superimposed using THESEUS and in PDB multimodel file format) analyzed in the soon to be submitted paper: superimposed_MD_trajectories.zip contains trajectories reported in the preprint and superimposed_MD_trajectories2.zip contains the results of subsequent simulations. </p>
X-ray crystallographic data of second extracellular domain of human tetraspanin CD9
<p>These X-ray diffraction data are of a crystal of the second extracellular domain of human tetraspanin CD9. The data show remarkable features that stem from twinning and concurrent diffuse scattering in streaked directions perpendicular to the twinning interface. The structure is described in [Oosterheert et al. (2020). Life Sci. Alliance, 3, e202000883] and is deposited in the PDB under accession code 6rlr.</p> <p>The raw data are described in details in IUCrData as a Raw Data Letter [Neviani et al., IUCrData (2022].</p> <p>The .h5 files are as they were originally recorded at Diamond Light Source at beamline I04. The images were converted to separate CBF files by a local script at DLS and compressed in the tar.bz2 file.</p>
Atomistic Fingerprint of Hyaluronan-CD44 Binding: Umbrella Sampling Data, Crystallographic Mode
<p>Simulation files (Gromacs 4.6.7 format) for the "Free Energy" simulations of crystallographic mode in Ref. [1]. </p> <p>Files include:</p> <p>-trajectories (.xtc) that are saved every 100ps <br> -initial structures (.gro), <br> -run input files (.tpr)<br> -simulation parameter files (.mdp)<br> -system topology file (.top)<br> -topology files included in the system topology file (.itp)</p> <p>'pullx' ('and pullx2' files, which contain data from the last 80ns) are used to constuct the free energy profile. Command for building the free energy profile is included in 'wham.sh'</p> <p>[1] Vuorio J. et al., Atomistic Fingerprint of Hyaluronan-CD44 Binding, PLOS Comp. Biol., 2017. (Submitted)</p>
X-ray diffraction data, crystallographic information file, infrared spectra, and LA-ICP-MS depthprofiles of davemaoite
<p>Calcium silicate perovskite, CaSiO3, is arguably the most geochemically important phase in the lower mantle, because it concentrates elements that are incompatible in the upper mantle, including the heat-generating elements thorium and uranium, which have half-lives longer than the geologic history of Earth. We report CaSiO3-perovskite as an approved mineral (IMA2020-12a) with the name davemaoite. The natural specimen of davemaoite proves the existence of compositional heterogeneity within the lower mantle. Our observations indicate that davemaoite also hosts potassium in addition to uranium and thorium in its structure. Hence, the regional and global abundances of davemaoite influence the heat budget of the deep mantle, where the mineral is thermodynamically stable.</p>
Data for Crystallographic orientation mapping of lizardite serpentinite by Raman spectroscopy
<p>The serpentine mineral lizardite displays strong Raman anisotropy in the OH-stretching region, resulting in significant wavenumber shifts (up to c. 14.5 cm <sup>-1</sup>) that depend on the orientation of the impinging excitation laser relative to the crystallographic axes. We quantified the relationship between crystallographic orientation and Raman wavenumber using well-characterised samples of Monte Fico lizardite by applying Raman spectroscopy and electron backscatter diffraction (EBSD) mapping on thin sections of polycrystalline samples and grain mounts of selected single crystals, as well as by a spindle stage Raman study of an oriented cylinder drilled from a single crystal. We demonstrate that the main band in the OH-stretching region undergoes a systematic shift that depends on the inclination of the c-axis of the lizardite crystal. The data are used to derive an empirical relationship between the position of this main band and the c-axis inclination of a measured lizardite crystal: y = 14.5 cos<sup>4 </sup>(0.013 x + 0.02) + (3670 ± 1), where y is the inclination of the c-axis with respect to the normal vector (in degrees) and x the main band position (wavenumber in cm <sup>-1</sup>) in the OH-stretching region. This new method provides a simple and cost-effective technique for measuring and quantifying the crystallographic orientation of lizardite-bearing serpentinite fault rocks, which can be difficult to achieve using EBSD alone. In addition to the samples used to determine the above empirical relationship, we demonstrate the applicability of the technique by mapping the orientations of lizardite in a more complex sample of deformed serpentinite from Elba Island, Italy.</p>
Data supporting "Influence of water on crystallographic preferred orientation patterns in a naturally-deformed quartzite"
<p>These files contain supporting data for the manuscript: "<span>Influence of water on crystallographic preferred orientation patterns in a naturally-deformed quartzite</span>", submitted to Solid Earth.</p> <p>1) an excel file containing FTIR data, aspect ratios, and crystallographic orientation data of quartz</p> <p>2) a powerpoint file containing a animated gif illustrating how quartz CPO in the studied sample changes with increasing water content</p>
Raw Data for: "Inorganic synthesis-structure maps in zeolites with machine learning and crystallographic distances"
<p>This repository contains all the raw data to reproduce the manuscript:</p> <p>D. Schwalbe-Koda et al. "Inorganic synthesis-structure maps in zeolites with machine learning and crystallographic distances". arXiv:2307.10935 (2023)</p> <p>The raw data should be used in combination with the code hosted on GitHub: <a href="https://github.com/dskoda/Zeolites-AMD">https://github.com/dskoda/Zeolites-AMD</a>.</p> <p><strong>Description of the data</strong></p> <p>The data in this link contains all necessary information to reproduce the manuscript. In combination with the code hosted on GitHub, it can be visualized and analyzed accordingly. The full description on the columns and results is available on the GitHub code.<br> The data files in this repository are:</p> <p>- `hparams_rnd_*.json`: results of the hyperparameter optimization of all classifiers studied in this work. The data was produced by randomly sampling the train-validation-test sets. In some cases, the data was normalized (`_norm_`), and the train set was kept `balanced` or `unbalanced`.<br> - `hyp_dm`: distance matrix of all hypothetical zeolites towards the known zeolites<br> - `hyp_predictions`: predictions of the synthesis conditions for all hypothetical zeolites<br> - `xgb_ensembles*`: pickle files containing the serialized ensemble models used in the evaluation of the data in this work. The models can be loaded with the `xgboost` Python package.</p> <p><strong>License</strong></p> <p>The data and all the content from this repository is distributed under the Creative Commons Attribution 4.0 (CC-BY 4.0)</p> <p>This work was produced under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.</p> <p>Dataset released as: LLNL-MI-854709.</p>
X-ray diffraction data, crystallographic information file, infrared spectra, and LA-ICP-MS depthprofiles of davemaoite
Open the record for dataset details and reuse information.
Reciprocal space reconstruction of X-ray crystallographic data of second extracellular domain of human tetraspanin CD9
<p>X-ray diffraction data of a crystal of CD9<sub>EC2</sub> are published on Zenodo with DOI: 10.5281/zenodo.5886687. From these data a reciprocal space reconstruction was generated with IMG2HKL as part of the EVAL software suite (http://www.crystal.chem.uu.nl/distr/eval/). It is written in ccp4 map format (https://www.ccp4.ac.uk/) and can be viewed with e.g. UCSF Chimera (https://www.cgl.ucsf.edu/chimera/). Details are described in IUCrData Raw Data Letters, Neviani et al. (2022).</p>
High resolution crystallographic and chemical characterisation of iodine induced stress corrosion crack tips formed in irradiated and non-irradiated zirconium alloys - Supporting data
<p>Data related to High resolution crystallographic and chemical characterisation of iodine induced stress corrosion crack tips formed in irradiated and non-irradiated zirconium alloys:</p> <p>Conor Gillen, Alistair Garner, Pia Tejland, Philipp Frankel,<br> High resolution crystallographic and chemical characterisation of iodine induced stress corrosion crack tips formed in irradiated and non-irradiated zirconium alloys, Journal of Nuclear Materials, Volume 519, 2019, Pages 166-172, ISSN 0022-3115,<br> https://doi.org/10.1016/j.jnucmat.2019.03.027.</p> <p>Datafiles for STEM-EDX analysis - STEM-EDX.zip</p> <p>Datafiles for TKD analysis - TKD.zip</p> <p>Datafiles for NanoSIMS analysis - 1: NanoSIMS raw data file (.im file) with all 160 planes and data for all ion signals acquired. Can be opened with the OpenMIMS plugin for ImageJ or other NanoSIMS software. 2: NanoSIMS processed data file (.nrrd file) which is drift corrected and can be opened with the OpenMIMS plugin for ImageJ</p>
Source Data for the publication "From crystallographic data to solution structure of photoreceptors: the case of AppA BLUF domain"
<p>This dataset contains the raw data for the results shown in the paper, all in excel format, one sheet per file:</p> <ul> <li> <p>chemical_shifts.xlsx - Chemical shifts of FMN and residues (on optimized frames)</p> </li> <li> <p>excitation_energies.xlsx - Excitation energies of FMN (on optimized frames)</p> </li> <li> <p>Distance_H3.xlsx - Distance between ASN-OD1 and FMN-H3 (on optimized frames)</p> </li> <li> <p>CO_freq_QMMM_MD.xlsx - Average C=O frequencies and relevant distances for each QM/MM MD.</p> <p> </p> </li> </ul>
Selenomethionine Macromolecular Crystallographic Data for Sep3-Agamous
<p>Macromolecular crystallographic selenomethionine data in CBF format with associated XDS.INP input file for processing in the XDS program. Data were collected on January 18 2022 on the ESRF microfocus beamline ID23-EH2 on a Dectris Pilatus3 2M detector.</p> <p>Dataset 4: 1.5x10^11 ph/s 4,4 micron beam FWHM 20 ms exposures</p> <p>Dataset 8: 1.5x10^11 ph/s 4,4 micron beam FWHM 30 ms exposures</p> <p> </p>
Data from: Predictive design of crystallographic chiral separation
Open the record for dataset details and reuse information.
Data: Crystallographic orientations of large hailstones
<p>The data are obtained from 6 hailstones, and are obtained from thin sections analyzed with an Automatic Texture Analyser (AITA).<br> The orientation data (c-axis orientations) are included in the file "orientation.dat", and the file "orientation.bmp" is a representation of the microstructure with a color-code related to the orientation.</p> <p>They can be easily treated with the open access too of Thomas Chauve (https://thomaschauve.github.io/aita/build/html/index.html) on Python.</p> <p>The author will provide any additionnal information required.</p>
Fig. 4. X-ray crystallographic data for 1 in Triterpenoids from Liquidambar Fructus induced cell apoptosis via a PI3KAKT related signal pathway in SMMC7721 cancer cells
Fig. 4. X-ray crystallographic data for 1.
Data for "Improving sampling of crystallographic disorder in Ensemble Refinement"
<p>Program outputs and data for "Improving sampling of crystallographic disorder in Ensemble Refinement"</p>
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