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380 results for “DIAMOND”
Diamond hits: Another lesson from unmapped reads – in depth analysis of RNA-Seq reads from various horse tissues
<p>Diamond hits - predicted peptides were compared against NCBI RefSeq protein (NR) databases using Diamond software</p> <p>Data: loin adipose - AD, hoof lamina - LM, liver - LI, longissimus muscle - LO, left lung - LU, heart left ventricle - LV, ovary- OV and parietal cortex – PC<br> 1 – horse ECA_UCD_AH1<br> 2 – horse ECA_UCD_AH2</p>
Diamond hits_1: Another lesson from unmapped reads – in depth analysis of RNA-Seq reads from various horse tissues
<p>Diamond hits - de novo assembled transcripts were compared against NCBI RefSeq Nucleotide (NT) using Diamond software</p> <p> </p> <p>Data: loin adipose - AD, hoof lamina - LM, liver - LI, longissimus muscle - LO, left lung - LU, heart left ventricle - LV, ovary- OV and parietal cortex – PC<br> 1 – horse ECA_UCD_AH1<br> 2 – horse ECA_UCD_AH2</p> <p> </p>
45° dataset from cubic insulin recorded at the I23 beamline of Diamond Light Source
<p>450 miniCBF X-ray diffraction images from a 45° rotation scan of a cubic insulin crystal recorded at the I23 beamline of Diamond Light Source as part of commissioning tests.</p> <p>This dataset is provided as a small, but complete, diffraction dataset from I23, which has the unique DECTRIS P12M detector. A simple script for processing the data using DIALS 3.10 is as follows:</p> <pre><code class="language-bash">dials.import first450/data_1_*.cbf\ fast_slow_beam_centre=1080,57,12 dials.find_spots imported.expt d_max=75 dials.index imported.expt strong.refl dials.refine indexed.{expt,refl} dials.integrate refined.{expt,refl} dials.symmetry integrated.{expt,refl} dials.scale symmetrized.{expt,refl} </code></pre> <p>The initial beam centre read from the image headers is not correct, so the corrected value is enforced on input in the above script.</p>
Multicrystal dataset of Lysozyme, collected at room temperature, using a multilayer monochromator on beamline VMXi, Diamond Light Source
<p>21 lysozyme crystals had 10 degrees of x-ray diffraction data collected on them and all data were automatically scaled and merged using xia2.multiplex. This file is the resultant dataset.</p>
Data and simulation files for: "Optimization of diamond optomechanical crystal cavities"
<p>Data and simulation files for the article "Optimization of diamond optomechanical crystal cavities".</p>
Evaluation of Slowfade Diamond as a Buffer for STORM Microscopy: raw data
<p>raw microscope data associated with the article "Evaluation of Slowfade Diamond as a Buffer for STORM Microscopy"</p> <p>See article for details about the imaging conditions.</p> <p> </p>
Early Diamond meets a late Wall
Crown Hall, Mies van der Rohe, 1956 Villa Savoye, Le Corbusier, 1931 Wall House, John Hejduk, 1973 Source: Objaverse 1.0 / Sketchfab
Diamond Ring
If you want to reduce the dimensions of the model, I will be happy to help you STL file has been fixed and ready for the print -STL File has been checked Software -No any bugs during printing The 3dm file is not suitable for printing and I just provided it for you to make changes. And I can help you if needed, but the rest of the files are ready to print If you need to make little changes to this model I'll do it for you no extra charge. If you have any questions I will be happy to answer them -If you are satisfied with the model, thank you for rating it[LIST] Source: Objaverse 1.0 / Sketchfab
Maison diamantée / Diamond house
3D digitization of the diamond house generated by the 3DF Zephyr v5.000 photogrammetry program 347 images. One of the oldest houses in Marseille, France. The diamond house is protected under historical monuments french law Numérisation de la maison diamantée en 3D générée par le programme de photogrammétrie 3DF Zephyr v5.000 processing 347 images. L'une des plus anciennes maison de Marseille, France. La maison diamantée est protégée au titre des [monuments historiques](https://www.pop.culture.gouv.fr/notice/merimee/PA00081365) Source: Objaverse 1.0 / Sketchfab
0.48 Angstrom 3,5-dinitrobenzoic acid (3,5-DNBA) C2/c polymorph single crystal X-ray diffraction data set recorded at Diamond Light Source I19-1
<p>Data set from 3,5-dinitrobenzoic acid (3,5-DNBA) C2/c polymorph recorded during in house research (DLS proposal: NR18193). Each run is saved as a single compressed tar file for convenience, runs 1, 2, 3 correspond to 3 x 170 degree omega scans at phi 0, 120, 240 degrees with 2-theta of 30 degrees, run 4 phi scan at 2-theta 0, runs 5-8 omega scans at 2-theta 55 degrees, giving data to 0.48A.</p> <p> </p> <p>Now including scale factor graph & report from processing</p>
A broadband pulse amplifier for Joule heating experiments in diamond anvil cells
<p>Voltage, current, and resistance timeseries for the submitted manuscript. The python script shows a simple example of how to load and plot data stored in the "..._processed.json" files. The spreadsheet describes the meanings of paramaters in the raw and processed data files.</p>
Updated example thaumatin data set from Diamond Light Source VMXi
<p>Example data set from the VMXi beamline at Diamond Light Source recorded in situ from a thaumatin crystal with processing results:</p> <p> </p> <pre>For AUTOMATIC/DEFAULT/NATIVE Overall Low High High resolution limit 1.85 5.02 1.85 Low resolution limit 50.49 50.50 1.88 Completeness 68.0 100.0 2.7 Multiplicity 3.3 3.9 1.0 I/sigma 12.9 24.8 1.4 Rmerge(I) 0.056 0.031 0.386 Rmerge(I+/-) 0.047 0.027 0.000 Rmeas(I) 0.065 0.035 0.545 Rmeas(I+/-) 0.061 0.035 0.000 Rpim(I) 0.032 0.017 0.386 Rpim(I+/-) 0.038 0.022 0.000 CC half 0.998 0.999 0.000 Wilson B factor 20.100 Anomalous completeness 58.0 99.8 0.1 Anomalous multiplicity 1.9 2.4 1.0 Anomalous correlation -0.015 -0.107 0.000 Anomalous slope 0.928 Total observations 53105 5240 32 Total unique 15898 1349 31 Assuming spacegroup: P 41 21 2 Other likely alternatives are: P 43 21 2 Unit cell (with estimated std devs): 58.6330(3) 58.6330(3) 151.4573(10) 90.0 90.0 90.0 </pre>
Diamond-BLASTx of transcriptome contigs of Thalassiosira hyalina and Nitzschia frigida
<p>This is an annotation file, delivering the Diamond-BLASTx results for the contigs of the transcriptome assemblies of Thalassiosira hyalina and Nitzschia frigida. Theswe originate from a time course experiment, in which these two species were exposed to high light stress and monitored over 120h under low and high pCO2. The corresponding Sequencing data is deposited at the EBI ArrayExpress database under accession number E-MTAB-6999. Contigs were created with Trinity Assembler and are available under DOI:10.5281/zenodo.3361258</p> <p>The according publication is currently in review (8/6/2019): Higher sensitivity towards light stress and ocean acidification in an Arctic sympagic compared to a pelagic diatom;</p> <p>Author team: Ane C. Kvernvik, Sebastian D. Rokitta, Eva Leu, Lars Harms, Tove M. Gabrielsen, Björn Rost and Clara J. M. Hoppe</p> <p>Do not hesitate to contact the authors if you like more information!</p>
Small example Eiger 2X 16M data set from Diamond Light Source I04
<p>Useful small (488 frame) Eiger data set recorded during routine testing, useful for software testing as it is small. Data recorded from a thaumatin crystal (unfortunate naming on my part) </p> <p> </p> <p>Revision includes screening images, and addition of name dataset in /entry/instrument</p> <p> </p> <pre>> h5dump -d /entry/instrument/name Therm_6_2.nxs HDF5 "Therm_6_2.nxs" { DATASET "/entry/instrument/name" { DATATYPE H5T_STRING { STRSIZE H5T_VARIABLE; STRPAD H5T_STR_NULLTERM; CSET H5T_CSET_ASCII; CTYPE H5T_C_S1; } DATASPACE SCALAR DATA { (0): "Macromolecular Crystallography I04" } } } </pre>
Small example Eiger 2X 16M data set from Diamond Light Source I04 revised for HDRMX Gold Standard Discussion
<p>Revised useful small (488 frame) Eiger data set recorded during routine testing, useful for software testing as it is small. Data recorded is from a thaumatin crystal by Graeme Winter, The original dataset is <a href="https://zenodo.org/record/3385862">https://zenodo.org/record/3385862</a> which contains two Eiger MX datasets, Therm_6_1 and Them_6_2, each with a data file and two versions each of the metadata -- a "..._master.h5" file and a "....nxs" file. The former are the usual Eiger metadata files using exposed external links to connect the metadata to the date, and the latter are HDF5-1.10 VDS files. This revision has the same data as the original Therm_6_2 data, but now includes with the "master.h5" file a "..._master_rev.h5" file and with the ".nxs" file a "..._rev.nxs" VDS file.</p> <p>The purpose to the changes in the "..._rev" files is to provide a supporting example for the HDRMX discusssion of a new proposed Eiger "gold standard" to improve the ability to process Eiger MX data collected at one facility at other facilties, by ensuring that sufficient metadata is stored with all datasets.</p> <p>The changes were made by the following script</p> <pre>cp Therm_6_2.nxs Therm_6_2_rev.nxs cp Therm_6_2_master.h5 Therm_6_2_master_rev.h5 export LD_LIBRARY_PATH=$HOME/lib export HDF5_PLUGIN_PATH=$HOME/lib export PATH=$HOME/bin:$PATH h5copy -i Therm_6_2_rev.nxs -o Therm_6_2_master_rev.h5 -s /entry/instrument/name -d /entry/instrument/name -f ref h5copy -i Therm_6_2_rev.nxs -o Therm_6_2_master_rev.h5 -s /entry/instrument/source -d /entry/source -f ref h5copy -i Therm_6_2_rev.nxs -o Therm_6_2_rev.nxs -s /entry/instrument/source -d /entry/source -f ref export end_time=`h5dump -d "/entry/end_time" Therm_6_2_master.h5 | grep ":" | sed 's/^.........//'|sed 's/.\$//'` echo "end_time: $end_time" python << 'EOL' import h5py import numpy as np import os end_time=os.environ['end_time'] fvds = h5py.File('Therm_6_2_rev.nxs','r+') fmaster = h5py.File('Therm_6_2_master_rev.h5','r+') fvds_keys=fvds.keys() fmaster_keys=fmaster.keys() fvds_entry=fvds['entry'] fmaster_entry=fmaster['entry'] fvds_entry_keys=fvds_entry.keys() fmaster_entry_keys=fmaster_entry.keys() fvds_entry_instrument=fvds['entry']['instrument'] fmaster_entry_instrument=fmaster['entry']['instrument'] fvds_entry_instrument_keys=fvds_entry_instrument.keys() fmaster_entry_instrument_keys=fmaster_entry_instrument.keys() fvds_entry_instrument_name=(fvds['entry']['instrument']['name']) fmaster_entry_instrument_name=(fmaster['entry']['instrument']['name']) fvds_entry_instrument_short_name=fvds_entry_instrument.attrs['short_name'] fmaster_entry_instrument_short_name=fmaster_entry_instrument.attrs['short_name'] zero_offset=fmaster_entry_instrument['detector']['module']['fast_pixel_direction'].attrs['offset'] fmaster_det_z=fmaster_entry_instrument['transformations']['det_z'] fvds_det_z=fvds_entry_instrument['transformations']['det_z'] print('fvds_keys: ',fvds_keys) print('fmaster_keys: ',fmaster_keys) print('fvds_entry_keys: ',fvds_entry_keys) print('fmaster_entry_keys: ',fmaster_entry_keys) print('fvds_entry_instrument_keys: ',fvds_entry_instrument_keys) print('fmaster_entry_instrument_keys: ',fmaster_entry_instrument_keys) print('fvds_entry_instrument_name: ',fvds_entry_instrument_name) print('fmaster_entry_instrument_name: ',fmaster_entry_instrument_name) print('fvds_entry_instrument_short_name: ',fvds_entry_instrument_short_name) print('fmaster_entry_instrument_short_name: ',fmaster_entry_instrument_short_name) print('fmaster_entry_instrument_detector_module_fast_pixel_direction_offset: ',zero_offset) print('fmaster_entry_instrument_detector_detector_z_det_z: ',fmaster_det_z) print('fmaster_entry_end_time: ',end_time) fmaster.attrs.modify('file_time',np.string_(end_time)) fmaster.attrs.modify('file_name',np.string_('Therm_6_2_master_rev.h5')) fmaster.attrs.modify('HDF5_Version',np.string_('hdf5-1.8.18')) fvds.attrs.modify('file_time',np.string_(end_time)) fvds.attrs.modify('file_name',np.string_('Therm_6_2_master_rev.h5')) fvds.attrs.modify('HDF5_Version',np.string_('hdf5-1.10.5')) fvds_entry_instrument_name.attrs.modify('short_name',np.string_(fvds_entry_instrument.attrs['short_name'])) fmaster_entry_instrument_name.attrs.modify('short_name',np.string_(fmaster_entry_instrument.attrs['short_name'])) fmaster_entry_instrument['attenuator']['attenuator_transmission'].attrs.modify('units',np.string_("")) fmaster_entry_instrument['detector']['count_time'].attrs.modify('units',np.string_("s")) fvds_entry_instrument_name.attrs.modify('short_name',np.string_(fvds_entry_instrument.attrs['short_name'])) fvds_entry_instrument['attenuator']['attenuator_transmission'].attrs.modify('units',np.string_("")) fvds_entry_instrument['detector']['count_time'].attrs.modify('units',np.string_("s")) fmaster_det_z.attrs.modify('offset',zero_offset) fvds_det_z.attrs.modify('offset',zero_offset) fmaster_entry['sample']['transformations']['phi'].attrs.modify('offset',zero_offset) fmaster_entry['sample']['transformations']['chi'].attrs.modify('offset',zero_offset) fmaster_entry['sample']['transformations']['sam_x'].attrs.modify('offset',zero_offset) fmaster_entry['sample']['transformations']['sam_y'].attrs.modify('offset',zero_offset) fmaster_entry['sample']['transformations']['sam_z'].attrs.modify('offset',zero_offset) fmaster_entry['sample']['transformations']['omega'].attrs.modify('offset',zero_offset) fvds_entry['sample']['transformations']['phi'].attrs.modify('offset',zero_offset) fvds_entry['sample']['transformations']['chi'].attrs.modify('offset',zero_offset) fvds_entry['sample']['transformations']['sam_x'].attrs.modify('offset',zero_offset) fvds_entry['sample']['transformations']['sam_y'].attrs.modify('offset',zero_offset) fvds_entry['sample']['transformations']['sam_z'].attrs.modify('offset',zero_offset) fvds_entry['sample']['transformations']['omega'].attrs.modify('offset',zero_offset) print(fmaster['entry']['instrument']['name'].attrs['short_name']) print(fmaster['entry']['instrument']['name'].attrs['short_name'].shape) print(fmaster['entry']['instrument']['name'].attrs['short_name'].dtype) del fvds_entry_instrument.attrs['short_name'] del fmaster_entry_instrument.attrs['short_name'] del fmaster_entry_instrument['source'] fvds.close() fmaster.close() quit() EOL $HOME/bin/nxvalidate -a NXmx -l /home/yaya/hdrmx_rev_29Sep19/hdrmx/definitions Therm_6_2_master_rev.h5 $HOME/bin/nxvalidate -a NXmx -l /home/yaya/hdrmx_rev_29Sep19/hdrmx/definitions Therm_6_2_rev.nxs </pre> <p>The revised cnxvalidate and definitions are available on github</p> <p><a href="https://github.com/HDRMX/cnxvalidate.git">https://github.com/HDRMX/cnxvalidate.git</a></p> <p><a href="https://github.com/HDRMX/definitions.git">https://github.com/HDRMX/definitions.git</a></p> <p> </p> <p> </p>
Fig. 42 in Diamonds in the rough: Ibotyporanga (Araneae, Pholcidae) spiders in semi-arid Neotropical environments
Fig. 42. Known geographic distribution of Brazilian species with plesiomorphic short procursus.
Cubic insulin data set collected from multiple lattices on i03 at Diamond Light Source
<p>Dataset collected as part of routine commissioning work, found to have more than one crystal present at the point where data were collected, allowing multiple lattices to be processed. </p> <p> </p> <p>While three lattices are present one is substantially weaker than the other two.</p> <p> </p> <p>Uploading to enable methods development and also to use for tutorials on how to use dials software.</p> <p> </p> <p>Processing data with the usual dials scripts (which will point to this deposition) result in statistics shown below. Tutorial to be uploaded to https://github.com/graeme-winter/dials_tutorials when available.</p> <p> </p> <p><code> -------------Summary of merging statistics-------------- </code></p> <p><code> Suggested Low High Overall</code><br><code>High resolution limit 1.51 4.10 1.51 1.48</code><br><code>Low resolution limit 54.89 54.93 1.54 54.89</code><br><code>Completeness 98.9 100.0 83.7 95.3</code><br><code>Multiplicity 54.7 78.1 4.6 53.5</code><br><code>I/sigma 18.9 89.2 0.3 18.4</code><br><code>Rmerge(I) 0.139 0.060 1.423 0.139</code><br><code>Rmerge(I+/-) 0.138 0.060 1.316 0.138</code><br><code>Rmeas(I) 0.140 0.061 1.590 0.140</code><br><code>Rmeas(I+/-) 0.140 0.060 1.609 0.140</code><br><code>Rpim(I) 0.016 0.007 0.683 0.016</code><br><code>Rpim(I+/-) 0.023 0.009 0.894 0.023</code><br><code>CC half 1.000 1.000 0.271 1.000</code><br><code>Anomalous completeness 97.8 100.0 67.8 92.3</code><br><code>Anomalous multiplicity 28.7 43.6 2.6 28.3</code><br><code>Anomalous correlation 0.038 0.276 -0.050 0.049</code><br><code>Anomalous slope 0.667 </code><br><code>dF/F 0.060 </code><br><code>dI/s(dI) 0.629 </code><br><code>Total observations 669615 52255 2342 670277</code><br><code>Total unique 12231 669 507 12529</code></p>
A large crystallographic dataset (3600 degrees) from insulin using an Eiger 2 XE 9M on I04-1 at Diamond Light Source Ltd
<p>3600 degree X-ray diffraction data set from cubic insulin taken on Diamond Beamline i04-1 with the Eiger 2 XE 9M detector at 500 Hz, for use by method developers to improve and streamline the analysis of large crystallographic datasets.</p>
Single-cell profiling of human bone marrow progenitors reveals mechanisms of failing erythropoiesis in Diamond-Blackfan anemia
<p>Ribosome dysfunction underlies the pathogenesis of many cancers and heritable ribosomopathies. Here we investigate how mutations in either ribosomal protein large (RPL) or ribosomal protein small (RPS) subunit genes selectively affect erythroid progenitor development and clinical phenotypes in Diamond-Blackfan anemia (DBA), a rare ribosomopathy with limited therapeutic options. Using single-cell assays of patient-derived bone marrow, we delineated two distinct cellular trajectories segregating with ribosomal protein genotypes: almost complete loss of erythroid specification were observed in <em>RPS</em>-DBA. In contrast, we observed relative preservation of qualitatively abnormal erythroid progenitors and precursors in <em>RPL</em>-DBA. Although both DBA genotypes exhibited a pro-inflammatory bone marrow milieu, <em>RPS</em>-DBA was characterized by erythroid differentiation arrest, whereas <em>RPL</em>-DBA was characterized by preserved GATA1 expression and activity. Compensatory stress erythropoiesis in <em>RPL</em>-DBA exhibited disordered differentiation underpinned by an altered glucocorticoid molecular signature, including reduced <em>ZFP36L2</em> expression<em>,</em> leading to milder anemia and improved corticosteroid response. This integrative analysis approach identified distinct pathways of erythroid failure and defined genotype-phenotype correlations in DBA. These findings may help facilitate therapeutic target discovery.</p> <p> </p>
Characterisation of unsteady flow in a 3D-printed Schwarz Diamond monolith using magnetic resonance velocimetry
<p>This data set contains the MRI velocity images presented in the article: Clarke, D, Galvosas, P, Holland, DJ. Characterization of unsteady flow in a 3D-printed Schwarz Diamond monolith using magnetic resonance velocimetry. <em>AIChE J</em>. 2023;e18097. doi:<a href="https://doi.org/10.1002/aic.18097">10.1002/aic.18097</a></p> <p>Images are in the .vtk format and may be viewed using suitable software (e.g. ParaView).</p> <p>*Description edited on 2023/04//21 to include eLocator.</p>
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