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60 results for “Crystallography”
Punta Telcio Zermatt-Saas Eclogite Mineral Data - Chemistry and Crystallography
<p>This dataset comprises location information, chemical data, and crystallographic data for a set of samples of deformed eclogites from the Punta Telcio region in the Northern Italian Alps. Data is focused on the chemistry and crystallography of the deformed omphacite in these eclogites. Crystallographic data consists of EBSD spaced point scans of eclogite thin sections, as well as EBSD grain maps of sections of some of these eclogite samples. Quantitative chemical data is provided for a series of omphacite grains on two eclogite samples, as well as for the amphibole and garnet phases in these samples. </p>
Data from: Comparative crystallography suggests maniraptoran theropod affinities for latest Cretaceous European ‘geckoid’ eggshell
Open the record for dataset details and reuse information.
Supporting information for IUCr survey on raw data archival and reuse in chemical crystallography
<p>Supporting information i.e. questions, responses and raw data, relating to a study into raw data management and availability in small molecule crystallography conducted under the auspices of the International Union of Crystallography Committee on Data.</p> <p>It is now common to deposit structure factors when publishing, which means that the small molecule crystallography community caters very well for routine structures. However this is generally only the case if everything in a raw image is fully and/or properly accounted for and the model is correct or appropriate. So for example, in some cases raw data may no longer be required, while in others it may be necessary to validate or ‘do better’ in the future. Moreover there are increasing pressures from bodies e.g. funders to make the data relating to research outputs Findable, Accessible, Interoperable and Reusable (FAIR). In acknowledgement of this situation and in order to begin addressing it, IUCr Journals now facilitate access to and citation of large raw diffraction datasets in its articles. Therefore it is important for our community understand and define how we manage our raw data in this respect.</p> <p>As Members of the IUCr Committee on Data we see the need to conduct this survey about exploring raw data archival<br> practice and gathering opinions as to if/how raw data could/should be used if it were to be made more widely<br> available.</p>
A series of pathological macromolecular crystallography datasets with twinning and other lattice disorders
<p>These 11 datasets were collected at the Diamond Light Source and belong to the same protein, NAL (N-acetyl neuraminic acid lyase), which crystallised in 4 different crystal forms from the same crystallisation conditions producing crystals with the same morphology. The file names, where applicable (10/11 cases), contain the corresponding PDB deposition code.</p>
Uncovering Protein Ensembles: Automated Multiconformer Model Building for X-ray Crystallography and Cryo-EM
<p>This respository corresponds to the following paper: Wankowicz et al. Uncovering Protein Ensembles: Automated Multiconformer Model Building for X-ray Crystallography and Cryo-EM (2024). These are the qFit models. MTZ and deposited models cna be downloaded from the PDB. </p>
Cryo-EM and X-ray crystallography ligands represented as 3D voxel grids for training deep learning models
<p>Ligand datasets used to train and evaluate the models studied in <em>"Ligand Identification using Deep Learning</em><em>"</em> by Karolczak, J. <em>et al.</em></p> <p>The blobs_full.tar.gz and cryoem_blobs.zip files contain compressed 3D numpy arrays (*.npz) of all the ligand blobs extracted from X-ray and cryo-EM PDB deposits prior to quality filtering. The npz file names correspond to the PDB ID, chain, residue number, and ligand name of the extracted blob. The cmb_data.csv file contains the tabular data used to train the CheckMyBlob model. The X-ray data were later divided into training and testing subsets according to the xray_train.csv and xray_holdout.csv files, respectively. The ligand_mapping.csv file contains the mapping from ligand IDs to ligand group names. Finally, the cryoem_qscores.csv file contains Q-scores that were used to filter cryo-EM ligands.</p>
PiezoTensorNet: Crystallography informed multi-scale hierarchical machine learning model for rapid piezoelectric performance finetuning
<h2>Description:</h2> <p>a. <strong>Feature Engineering</strong>:</p> <p> The file <strong>data_of_145_features.csv</strong> consists of the datasets of the features. The datasets correspond to Fig. 1(a) of the paper.</p> <p>b. <strong>HierCrystalNet of PiezoTensorNet</strong>:</p> <p> The saved models after training HierCrystalNet are placed inside the zip folders, namely, (i)<strong> classification_saved_models.zip</strong>, (ii) PG1_cubic_saved_models.zip, (iii) PG2_tetragonal42m_saved_models.zip, (iv) PG3_orthorhombic222_saved_models.zip, (v) PG4_hex6tetra4mm_saved_models.zip, and (vi) PG5_orthorhombicmm2_saved_models.zip.</p> <p>c. <strong>ModularEnsembleNet of PiezoTensorNet </strong>:</p> <p> The prediction_results.zip folder consists the prediction results of the ModularEnsembleNet. </p> <p>d. <strong>Input data of piezoelectric tensors and stiffness tensors for the</strong> <strong>finite element analysis</strong>: </p> <p>(i) <em><strong>piezoelectric_tensors_AlN_B0.3Er0.5Al0.2N_alloy.zip</strong></em>: The coefficients of piezoelectric tensors (array shape: 3x6) for AlN alloy and B0.3Er0.5Al0.2N alloy are respectively presented in <strong>undoped_AlN_piezoelectric_tensor.csv</strong> and <strong>B0.3Er0.5Al0.2N_alloy_unrotated_piezoelectric_tensor.csv</strong> files. Both of these files contain the data for samples whose laboratory coordinate system is same with that of the orientation of crystal lattice (all of the three Euler angles theta, psi and phi = 0 degree ), and so the compositional effect on the piezoelectric behavior can be assessed solely without considering the orientation effect. Rotation or other transformation can cause the vector value of (theta, phi, phis) other than (0,0,0) which indicates that the laboratory coordinate system of a sample being different than its lattice orientation. The effect of two different magnitudes of rotation on the coefficients of piezoelectric tensors for B0.3Er0.5Al0.2N alloy are revealed through the files <strong>B0.3Er0.5Al0.2N_alloy_rotated_at_orientation_1_piezoelectric_tensor.csv</strong> and <strong>B0.3Er0.5Al0.2N_alloy_rotated_at_orientation_2_piezoelectric_tensor.csv</strong>. Orientation 1 refers to<strong> theta = 0 degree, psi = 268.47 degree, 91.52 degree, 0 <= phi <= 360 degree</strong> whereas <strong> theta = 180 degree, psi = 268.47 degree, 91.52 degree, 0 <= phi <= 360</strong> for orientation 2. The units of the coefficients are C/m^2. The description of the methodology on how to generate this data in this format is provided at https://piezoelectrictensorsdatabase.streamlit.app/ .</p> <p>(ii) <em><strong>stiffness_tensors_AlN_B0.3Er0.5Al0.2N_alloy.csv</strong></em>: The stiffness tensors (array shape: 6x6) for the two materials AlN alloy and B0.3Er0.5Al0.2N alloy at room temperature are presented through the four csv files. The elements of stiffness tensors in the datasets are presented in GPa. The Cijkl tensors are provided first for isotropy and then for orthotropy assumptions. The description of these tensors for AlN and B0.3Er0.5Al0.2N materials are provided in the web apps: https://isotropic-elasticity.streamlit.app/ and https://orthotropic-elasticity.streamlit.app/</p>
A series of pathological macromolecular crystallography datasets with twinning and other lattice disorders - part II
<p>This entry is linked to a previous deposition with DOI : 10.5281/zenodo.54568 which is discussed in the same manuscript </p> <p> </p>
CrystalWalk record at International Union of Crystallography (IUCR)'s crystallographic software database
<p>CrystalWalk record at International Union of Crystallography (IUCR)’s crystallographic software database</p> <p>Original URL available at <a href="https://www.iucr.org/resources/other-directories/software/crystalwalk">https://www.iucr.org/resources/other-directories/software/crystalwalk</a></p> <p>Mirrors <a href="https://archive.fo/6I1lu">here </a>and <a href="https://web.archive.org/web/20180911142529/https://www.iucr.org/resources/other-directories/software/crystalwalk">here</a></p>
USP Zf-UBD Crystallography Pipeline
<p>The design, cloning, purification and crystallization of protein constructs of USP Zf-UBD’s for X-ray structure determination</p>
Raw Data from Fluoroacetate Dehalogenase Solved by Serial Oscillation Crystallography (1° oscillation per crystal), PDB 6MUH
<p>This is the raw data for PDB 6MUH: Fluoroacetate dehalogenase, room temperature structure solved by serial 1 degree oscillation crystallography.</p> <p>Data was taken at Beamline G3 of CHESS at 10.2 keV (1.2155 Å). Collection date was 2018-03-04. Beam size 7 µm V x 9 µm H, flux 2e11 ph/s. Detector: Dectris EIGER X 1M. Data format: Dectris HDF5 for EIGER. Rotation was counterclockwise about the laboratory Z-axis ( 0 -1 0 in the XDS coordinate system). Detector distance was 45 mm.</p> <p>One degree from each data well was collected, at 0.2° per frame. Each well has five data frames. Data was collected in four successive iterations, labeled 000-003, of 1600 wells; each *master.h5 corresponds to 8000 data frames. </p>
Expression test and purification of SETDB1 catalytic domain constructs' for structural studies by X-ray crystallography.
<p><strong>Experiment: </strong>Expression test and purification of SETDB1 catalytic domain constructs’ for structural studies by X-ray crystallography.</p> <p><strong>Aim:</strong> In the present section of this study, we focused on the development of efficient bacterial expression systems to produce large amounts of soluble SETDB1 catalytic domain for structural studies. This report involves a summary of expression test results of different fragments of SETDB1 and purification of various fusion proteins.</p>
UK National Crystallography Service benchmark experiment 1
<p>Data part of a bench-marking experiment.</p> <p>Data collected at Diamond Light Source, beamline I19.</p> <p>sample: 'challenging'</p> <p>sum formula: C13 H6 F5 N</p> <p>Wavelength: 0.6889 Angstrom</p> <p>Temperature: 100K</p> <p>Data integrated with Crysalis PRO</p> <p> </p>
UK National Crystallography Service benchmark experiment 2
<p>Data part of a bench-marking experiment.</p> <p>Data collected at National Crystallography Service, Southampton.</p> <p>sample: 'challenging'</p> <p>sum formula: C13 H6 F5 N</p> <p>Wavelength: 0.71075 Angstrom</p> <p>Temperature: 100K</p> <p>Data integrated with Crysalis PRO</p>
UK National Crystallography Service benchmark experiment 3
<p>Data part of a bench-marking experiment.</p> <p>Data collected at Diamond Light Source, beamline I19.</p> <p>sample: 'easy'</p> <p>sum formula: C20 H16 N2 O2</p> <p>Wavelength: 0.6889 Angstrom</p> <p>Temperature: 100K</p> <p>Data integrated with DIALS using XIA2</p>
X-ray crystallography datasets for the F420-reducing sulfite-reductase from Methanocaldococcus jannaschii and Methanothermococcus thermolithotrophicus
<p>The three datasets present in this entry are all related to X-ray crystallography data collected from crystals of the F<sub>420</sub>-reducing sulfite-reductase (Fsr) from <em>Methanocaldococcus jannaschii</em> (Mj) and <em>Methanothermococcus thermolithotrophicus</em> (Mt).</p> <p>MjFsr_Fe_Kedge.zip: Dataset collected at a wavelength of 1.74013 Å. Fsr from <em>Methanocaldococcus jannaschii.</em></p> <p>MjFsr.zip: Dataset collected at a wavelength of 0.97857 Å. Fsr from <em>Methanocaldococcus jannaschii.</em></p> <p>MtFsr.zip: Datasets collected at a wavelength of 1.00004 Å. Fsr from <em>Methanothermococcus thermolithotrophicus.</em></p>
Data from: Ontogenetic variability in crystallography and mosaicity of conodont apatite: Implications for microstructure, paleothermometry and geochemistry
<p>X-ray diffraction data from Silurian conodonts belonging to various developmental stages of the species <i>Dapsilodus obliquicostatus </i>demonstrate changes in crystallography and degree of nanocrystallite ordering (mosaicity) in both hyaline and albid crown tissue. The exclusive use of a single species in this study, combined with systematic testing of each element type at multiple locations, provided insight into microstructural and crystallographic differentiation between element position (S<sub>a</sub>, S<sub>b-c</sub>, M) as well as between juveniles and adults. A relative increase in the unit cell dimensions of the <i>a</i>-axis/<i>c</i>-axis ratio of nanocrystallites during growth was apparent in areas demonstrating single-crystal behavior but no such relationship was seen in dominantly polycrystalline areas. Systematic variations in mosaicity were identified, with mosaicity (as a proxy for disorder) increasing during growth, as well as along elements from tip to base. These results provide potential insight into the integrity of conodont apatite as a recorder of paleoseawater chemistry, as well as demonstrate the need to consider the influence of ontogeny and element position on the use of conodonts in paleothermometry and geochemical investigations. </p>
Nanoscale Phase Segregation in Supramolecular π‑Templating for Hybrid Perovskite Photovoltaics from NMR Crystallography
<p>Raw and processed NMR data, molecular dynamics data, structure files, photovoltaic data, and additional characterisation data for Nanoscale Phase Segregation in Supramolecular π‑Templating for Hybrid Perovskite Photovoltaics from NMR Crystallography, DOI: 10.1021/jacs.0c11563. For more details see README file. </p> <p>NMR_data.zip: Raw and processed NMR data in the file structure of the TopSpin software, which is available from Bruker. </p> <p>NMR_calculations.zip: The input and output Quantum Espresso files are given for both the single point (*.scf.in and *.scf.out) and NMR calculations (*.nmr.in and *.nmr.out).</p> <p>cif_files_all_structures.zip: All structures in cif format. </p> <p>MD_*.zip: MD trajectories of (PEA)2PbI4, (FEA)2PbI4 and configuration 1 of (PF)2PbI4. The full trajectories are given in dcd format which can be opened using the VMD software. The trajectories are also shown as movies. </p> <p>PV+characterisation.zip: The data for the photovoltaic analysis, XPS spectra and XRD patterns in Excel format. </p>
Reconciling ASPP-p53 Binding Mode Discrepancies through an Ensemble Binding Framework that Bridges Crystallography and NMR Data
<p>The trajectory of 'Reconciling ASPP-p53 Binding Mode Discrepancies through an Ensemble Binding Framework that Bridges Crystallography and NMR Data'</p>
Massive Compression for High Data Rate Macromolecular Crystallography (HDRMX): Impact on Diffraction Data and Subsequent Structural Analysis: Subset with data from 2 deposited PDBs.
<p>Diffraction data from a lysozyme crystal. Data collected at 7.5 keV at the AMX beamline, NSLS-II. 360 degrees were collected, with 0.2 deg per frame. This data set contains 2 folders; 1 from uncompressed data and 1 from data compressed using lossy compression as follow: frames were summed (2x), pixels were binned (2x) and Hcompress with level 24 was applied to uncompressed data. </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.