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Dataset results
339 results for “raw images”
Raw diffraction images of the crystal structure of human VISTA extra cellular domain in complex with Fab fragment of pH-selective anti-VISTA antibody
<p>The diffraction datasets was collected at X10SA, SLS. The dataset was collected from one crystal using a rotation scheme for 222º oscillation with the following experimental parameters; Wavelength: 0.9998 Å, Detector: EIGER2 Si 16M (DECTRIS Co. Ltd.). The crystal belonged to space group C 1 2 1 with unit cell parameters a=207.66, b=39.51, c=177.98 Å, and beta=117.12°.</p><p>PDB ID: 8TBQ</p>
Serial Isomorphous Replacement Data -Pilatus3 2M raw images and meta data
<p>Diffraction data collected from the ESRF ID23-EH2 microfocus beamline for the purpose of single isomorphous replacement phasing. These are raw CBF images from a pilatus3 2M detector. The "process" sub directory and CBF headers contain meta data about the experimental setup. Data were collected with the Mesh and Collect workflow and contain partial datasets of ~10 degrees with 0.1 degree oscillations (more detail in the meta data files). </p>
Computer Code; Raw Image_Mangoes
<p>Exporting mangoes to foreign countries while maintaining quality is a challenge for distributors. The quality and maturity of mangoes are inhomogeneous, even when mangoes are harvested from the same tree at the same time. While quality affects the product value at the time of harvest, maturity affects the product value over time after harvest. The maturity of mangoes also greatly affects the storage and transport time. This data is collected in Vietnam with many mango cultivars and used to train machine learning models for the automatic classify mango system.</p>
Live cell microscopy: From image to insight - raw data & analysis
<p>Accompanying raw and processed data as well as analysis scripts for the publication Biophysics Rev. 3, (2022); <a href="https://doi.org/10.1063/5.0082799">10.1063/5.0082799</a> "Live cell microscopy: From image to insight".</p>
Raw data accompanying the manuscript "Cost-effective high-speed, three-dimensional live-cell imaging of HIV-1 transfer at the T cell virological synapse"
<p>These are the raw datasets used to generate the figures for the manuscript entitled "Cost-effective high-speed, three-dimensional live-cell imaging of HIV-1 transfer at the T cell virological synapse". The data files are 3D image stacks of a custom-built wide field deconvolution fluorescence microscope (.tif) and super-resolution structured illumination microscopy data (.dv) of Jurkat T cells transferring HIV-1 virus particles to previously uninfected primary T cells.</p>
Raw diffraction images of lysophosphatidic acid receptor LPA6
<p>LPA<sub>6</sub> is a class A G protein-coupled receptor which recognizes lysophosphatidic acid, a lipid mediator, as its ligand. The crystallization construct consists of zebrafish lysophosphatidic acid receptor LPA<sub>6</sub> and T4 lysozyme fused within the intracellular loop 3 of LPA<sub>6</sub>. The crystals were obtained within the lipidic cubic phase. No synthetic chemical compounds were added for the crystallization.</p> <p>397 small-wedge (4° or 6°/crystal) datasets collected from loop-harvested microcrystals using EIGER X 9M detector at a wavelength of 1 Å on BL32XU, SPring-8. The crystals belonged to space group P2<sub>1</sub>2<sub>1</sub>2<sub>1</sub> with unit cell parameters a=55.9, b=65.0, c=160.7 Å.</p> <p>241 datasets were merged at 3.2 Å resolution in the published result (Taniguchi et al. Nature 2017; PDB code: 5XSZ) using KAMO; see processing note https://github.com/keitaroyam/yamtbx/wiki/Processing-LPA6-data-(5XSZ)</p> <p>NOTE</p> <ul> <li> <p>flatfield correction was not applied to the images and you need to apply it using the correction table saved in master.h5 files.</p> </li> <li> <p>master.h5 files were modified; see https://github.com/keitaroyam/yamtbx/blob/master/doc/eiger-en.md</p> </li> <li> <p>Most frames have lipid rings and some have ice rings.</p> </li> </ul>
Raw diffraction images of endothelin ETB receptor bound to clinical antagonist bosentan and its analog
<p>Diffraction images of endothelin ET<sub>B</sub> receptor bound to bosentan (PDB code 5XPR) and K-8794 (5X93).</p> <p>Bosentan is an oral medication approved for the treatment of pulmonary arterial hypertension. K-8794 is the ETB-selective high-affinity analog of bosentan.</p> <p>Two datasets of 5X93 were collected with helical method, while for 5XPR 16 small-wedge (10°/crystal) datasets were collected automatically using ZOO system. In both cases the diffraction images were collected from loop-harvested microcrystals using MX225HS CCD detector at a wavelength of 1 Å on BL32XU, SPring-8.</p> <p>For 5XPR, 14 datasets were merged at 3.6 Å resolution in the published result (Shihoya et al. NSMB 2017) using KAMO; see processing note: https://github.com/keitaroyam/yamtbx/wiki/Processing-ETBR-bonsentan-data-(5XPR)</p> <p>NOTE</p> <ul> <li> <p>Most frames have (relatively weak) lipid rings.</p> </li> </ul> <ul> <li> <p>There is the indexing ambiguity problem in 5XPR (space group P3<sub>2</sub>21) that should be resolved before merging.</p> </li> <li> <p>5xpr_bosentan/bosentan-1425-01/multi_002_000019.img.bz2 is missing (probably due to a detector problem)</p> </li> </ul>
Raw diffraction images of eukaryotic MATE transporter (AtDTX14)
<p>Multidrug And Toxic compound Extrusion (MATE) transporter exports xenobiotics by using the gradient of H<sup>+</sup>. The crystals were obtained within the lipidic cubic phase.</p> <p>288+85 (Auto+manual) small-wedge (5-20°/crystal) datasets collected from loop-harvested microcrystals using MX225HS CCD detector at a wavelength of 1 Å on BL32XU, SPring-8. The crystals belonged to space group P2<sub>1</sub>2<sub>1</sub>2<sub>1</sub> with unit cell parameters a=52.8, b=86.8, c=116.4 Å.</p> <p>100 datasets were merged at 2.6 Å resolution in the published result (Miyauchi et al. Nature Communications, 2017; PDB code: 5Y50) using KAMO; see processing note https://github.com/keitaroyam/yamtbx/wiki/Processing-AtDTX14-data-(5Y50)</p> <p>Note that most frames have lipid rings.</p>
Raw diffraction images of human orexin 2 receptor bound to the subtype-selective antagonist EMPA
<p>Human orexin 2 receptor (OX2R) is a member of G protein-coupled receptors (GPCR). OX2R plays important roles in modulating feeding behavior and regulating the sleep-wake cycle.</p> <p>805 small-wedge (1-6°/crystal) datasets collected from loop-harvested microcrystals using MX225HS CCD detector at a wavelength of 1 Å on BL32XU, SPring-8. The crystals belonged to space group C2 with unit cell parameters a=94.1, b=75.5, c=95.9 Å, β=111.4°.</p> <p>631 datasets were merged at 1.96 Å resolution in the published result (Suno et al. Structure 2017; PDB code: 5WQC) using KAMO; see https://github.com/keitaroyam/yamtbx/wiki/Processing-OX2R-data-(5WQC)</p> <p>Note</p> <ul> <li>Most frames have lipid rings.</li> <li>One dataset (not included in the published result) was lost for some reason (so 804 datasets are available).</li> </ul>
Raw diffraction images of leukotriene B4 receptor BLT1
<p>Diffraction images of Leukotriene B<sub>4</sub> receptor (BLT1) in complex with antagonist BIIL260, a chemical bearing a benzamidine moiety. BLT1 is one of class-A G-protein coupled receptor (GPCR), and the bound benzamidine moiety mimics a sodium ion-centered water cluster of BLT1 that is considered to exist in many class-A GPCRs. The bound benzamidine moiety stabilizes the inactive state of BLT1, and BIIL260 exhibits the characteristics of an inverse agonist for BLT1.</p> <p>Small-wedge (1296 crystals, 2.5°/crystal) datasets collected from loop-harvested microcrystals using EIGER X 9M detector at a wavelength of 1 Å on BL32XU, SPring-8. The crystals belonged to space group P22<sub>1</sub>2<sub>1</sub> with unit cell parameters a=69.6, b=77.6, c=135.5 Å.</p> <p>Finally, 494 datasets were merged at 3.7 Å resolution in the published result (Hori et al. Nature Chemical Biology, 2018; PDB code: 5X33) using KAMO; see processing note https://github.com/keitaroyam/yamtbx/wiki/Processing-BLT1-data-(5X33)</p> <p>Note</p> <ul> <li>The master.h5 files were modified; see https://github.com/keitaroyam/yamtbx/blob/master/doc/eiger-en.md</li> <li>To further reduce total file size, flatfield data of master.h5 were removed and saved in a file in each directory (linked from master.h5 files).</li> <li>Most frames have lipid rings.</li> </ul>
Raw images and processed datasets related to the journal article Robust Assessment of Post-Localisation Hardening Behaviour in Eurofer97 using Inverse Finite Element Methods
Open the record for dataset details and reuse information.
Raw data for: Use the 4S (Signal-Safe Speckle Subtraction): Explainable Machine Learning reveals the Giant Exoplanet AF Lep b in High-Contrast Imaging Data from 2011
<p>This collection of data contains all raw data needed to reproduce the results in the paper:</p> <p>Use the 4S (Signal-Safe Speckle Subtraction): Explainable Machine Learning reveals the Giant Exoplanet AF Lep b in High-Contrast Imaging Data from 2011</p> <p>It can also be used as a demonstration dataset for our Python package fours.</p> <p>More details can be found in the online documentation of our python package:<br><a href="https://fours.readthedocs.io/en/latest/">https://fours.readthedocs.io/en/latest/</a></p>
Repository 2 of 2 of the Level 0 (raw FITS) images from the DMI Mauna Loa Earthshine telescope experiment (2010-2012)
<h2>Raw data upload</h2> <p>These are tar files of the raw data obtained with the earthshine refractor conceived, designed and built by Danish Meteorological Institute and Lunds Observatory and operated on Mauna Loa at the NOAA observatory during 2011-2012.</p> <p>The present doi relates to one of two - each one holds roughly 50Gb tar file. Get all for the complete dataset. The other doi is: 10.5281/zenodo.11442378</p> <p>The data are in the form of FITS files. There are data for 5 different photometric filters - Johnson B and V and then 3 red or nIR filters - IRCUT, VE1 and VE2. Some frames are without filters.</p> <p>Examples:</p> <p>2455945.1760145MOON_B_AIR.fits.gz - image of the Moon through the B filter</p> <p>2455945.0413946DARK_DARK.fits.gz - a DARK frame image taken with same exposure time as the adjacent MOON image. <br>A DARK is typically taken before and after all MOON images.</p> <p>The file-naming strategy for the file inside the archive files is simple - names start with the (fractional) Julian day of the observation, followed by target name and two indicators of the filters or other light-path devices that were used, e.g.: _VE1_AIR indicates the VE1 colour filter with just 'air' (ie nothing) in the second option. The second option may include names of knife-edge devices or neutral density filters that could be inserted.</p> <p>There are also some FLAT images taken on inside of dome or of the sky or of the Hohlraum source.</p> <p>The MOON images may well be 100-image 3D-cubes taken within a minute or two.</p> <p>Future upgrades (in new dois, but in this Community) will include dark-frame subtracted, aligned and averaged images (Level 1). A Level 2 may include actual model fits of the full lunar disks, in which terrestrial albedo is a model-parameter.</p> <p>The file called "index_justJD.csv" lists which Julian days are present in which archive file. Note that some days are spread over several tar files.</p> <p>The images were acquired with the remotely-operated telescope by Peter Thejll, Hans Gleinser, Chris Flynn, as well as Henriette Schwarz.</p> <p>Notes updated May 3 2024.</p> <p>Peter Thejll</p> <p>write pth@dmi.dk for queries</p>
Repository 1 of 2 of the Level 0 (raw FITS) images from the DMI Mauna Loa Earthshine telescope experiment (2010-2012)
<h2>Raw data upload</h2> <p>These are tar files of the raw data obtained with the earthshine refractor conceived, designed and built by Danish Meteorological Institute and Lunds Observatory and operated on Mauna Loa at the NOAA observatory during 2011-2012.</p> <p>The present doi relates to one of two - each one holds roughly 50Gb tar file. Get all for the complete dataset. The other doi is: 10.5281/zenodo.11500335</p> <p>The data are in the form of FITS files. There are data for 5 different photometric filters - Johnson B and V and then 3 red or nIR filters - IRCUT, VE1 and VE2. Some frames are without filters.</p> <p>Examples:</p> <p>2455945.1760145MOON_B_AIR.fits.gz - image of the Moon through the B filter</p> <p>2455945.0413946DARK_DARK.fits.gz - a DARK frame image taken with same exposure time as the adjacent MOON image. <br>A DARK is typically taken before and after all MOON images.</p> <p>The file-naming strategy for the file inside the archive files is simple - names start with the (fractional) Julian day of the observation, followed by target name and two indicators of the filters or other light-path devices that were used, e.g.: _VE1_AIR indicates the VE1 colour filter with just 'air' (ie nothing) in the second option. The second option may include names of knife-edge devices or neutral density filters that could be inserted.</p> <p>There are also some FLAT images taken on inside of dome or of the sky or of the Hohlraum source.</p> <p>The MOON images may well be 100-image 3D-cubes taken within a minute or two.</p> <p>Future upgrades (in new dois, but in this Community) will include dark-frame subtracted, aligned and averaged images (Level 1). A Level 2 may include actual model fits of the full lunar disks, in which terrestrial albedo is a model-parameter.</p> <p>The file called "index_justJD.csv" lists which Julian days are present in which archive file. Note that some days are spread over several tar files.</p> <p>The images were acquired with the remotely-operated telescope by Peter Thejll, Hans Gleinser, Chris Flynn, as well as Henriette Schwarz.</p> <p>Notes updated May 3 2024.</p> <p>Peter Thejll</p> <p>write pth@dmi.dk for queries</p>
Nissl_4, Raw images for Machine learning for histological annotation and quantification of cortical layers.
<p>This dataset contains some images (TIFF image data) of <strong>brain juvenile rats Wistar Han (P14)</strong> scanned immunostained slides by using an automated slide scanner (Olympus, VS120-L100, GER) equipped with a UPLSAPO 20x/0.75 air objective (Olympus, GER) and a Pike F505 Color camera leading to a pixel size of 0.346 μm/pixel.</p> <p>These raw images are part of another Zenodo dataset <span><a href="https://doi.org/10.5281/zenodo.11544829" target="_blank" rel="noopener noreferrer">https://doi.org/10.5281/zenodo.11544829</a></span>, that contains the QuPath projects that uses this dataset and 5 others (from Nissl_1 to Nissl_6).</p>
Nissl_3, Raw images for Machine learning for histological annotation and quantification of cortical layers.
<p>This dataset contains images (TIFF image data) of <strong>brain juvenile rats Wistar Han (P14)</strong> scanned immunostained slides by using an automated slide scanner (Olympus, VS120-L100, GER) equipped with a UPLSAPO 20x/0.75 air objective (Olympus, GER) and a Pike F505 Color camera leading to a pixel size of 0.346 μm/pixel.</p> <p>These raw images are part of another Zenodo dataset <span><a href="https://doi.org/10.5281/zenodo.11544829" target="_blank" rel="noopener noreferrer">https://doi.org/10.5281/zenodo.11544829</a></span>, that contains the QuPath projects that uses this dataset and 5 others (from Nissl_1 to Nissl_6).</p>
Nissl_2, Raw images for Machine learning for histological annotation and quantification of cortical layers.
<p>This dataset contains images (TIFF image data) of <strong>brain juvenile rats Wistar Han (P14)</strong> scanned immunostained slides by using an automated slide scanner (Olympus, VS120-L100, GER) equipped with a UPLSAPO 20x/0.75 air objective (Olympus, GER) and a Pike F505 Color camera leading to a pixel size of 0.346 μm/pixel.</p> <p>These raw images are part of another Zenodo dataset <span><a href="https://doi.org/10.5281/zenodo.11544829" target="_blank" rel="noopener noreferrer">https://doi.org/10.5281/zenodo.11544829</a></span>, that contains the QuPath projects that uses this dataset and 5 others (from Nissl_1 to Nissl_6).</p>
Nissl_1, Raw images for Machine learning for histological annotation and quantification of cortical layers.
<p>This dataset contains images (TIFF image data) of <strong>brain juvenile rats Wistar Han (P14)</strong> scanned immunostained slides by using an automated slide scanner (Olympus, VS120-L100, GER) equipped with a UPLSAPO 20x/0.75 air objective (Olympus, GER) and a Pike F505 Color camera leading to a pixel size of 0.346 μm/pixel.</p> <p>These raw images are part of another Zenodo dataset <span><a href="https://doi.org/10.5281/zenodo.11544829" target="_blank" rel="noopener noreferrer">https://doi.org/10.5281/zenodo.11544829</a></span>, that contains the QuPath projects that uses this dataset and 5 others (from Nissl_1 to Nissl_6).</p> <p> </p>
Nissl_6, Raw images for Machine learning for histological annotation and quantification of cortical layers.
<p>This dataset contains images (TIFF image data) of <strong>brain juvenile rats Wistar Han (P14)</strong> scanned immunostained slides by using an automated slide scanner (Olympus, VS120-L100, GER) equipped with a UPLSAPO 20x/0.75 air objective (Olympus, GER) and a Pike F505 Color camera leading to a pixel size of 0.346 μm/pixel.</p> <p>These raw images are part of another Zenodo dataset <span><a href="https://doi.org/10.5281/zenodo.11544829">https://doi.org/10.5281/zenodo.11544829</a></span>, that contains the QuPath projects that uses this dataset and 5 others (from Nissl_1 to Nissl_6).</p> <p> </p> <p> </p>
Nissl_5, Raw images for Machine learning for histological annotation and quantification of cortical layers
<p>This dataset contains images (TIFF image data) of <strong>brain juvenile rats Wistar Han (P14)</strong> scanned immunostained slides by using an automated slide scanner (Olympus, VS120-L100, GER) equipped with a UPLSAPO 20x/0.75 air objective (Olympus, GER) and a Pike F505 Color camera leading to a pixel size of 0.346 μm/pixel.</p> <p>These raw images are part of another Zenodo dataset <span><a href="https://doi.org/10.5281/zenodo.11544829" target="_blank" rel="noopener noreferrer">https://doi.org/10.5281/zenodo.11544829</a></span>, that contains the QuPath projects that uses this dataset and 5 others (from Nissl_1 to Nissl_6).</p>
ScienceDex guides
Understand access before you commit
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.