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2,014 results for “Resolvers”
Chromosome-scale, haplotype-resolved genome assembly of Suaeda glauca
<p><em>Suaeda glauca</em>is an annual herb of Suaeda and an important saline-alkali plant resource, which is widespread on beaches and saline lands around the world. It is also a good candidate for food, feed, and drug development. There has been no publication of the <em>Suaeda glauca</em>genome assembly, limiting the evolutionary study of Amaranthaceae and the bioavailability of <em>Suaeda glauca</em>.</p> <p>Using PacBio HiFi and Hi-C sequencing data, we successfully generated chromosome-scale, haplotype-resolved assemblies of the <em>Suaeda glauca</em>genome. The size of the final primary assembly was 622.95 Mb, and the contig N50 was 19.42 Mb, which was successfully anchored to 9 chromosomes, accounting for 96.79% of the total assembly size. The repeat content and genome size of <em>Suaeda glauca</em>are much higher than those of the same genus <em>Suaeda aralocaspica</em>, presumably due to a recent burst of LTR insertions. Using HiFi reads, we assembled the complete circular chloroplast genome of <em>Suaeda glauca</em>. Through gene family and phylogenetic tree analysis, it was shown that <em>Suaeda glauca</em>and <em>Suaeda aralocaspica</em>differentiated at ~26.36 million years ago (MYA), and Amaranthaceae species began to differentiate at ~52.00 MYA.</p>
Laser scan and polarization resolved Fourier-plane measurements of nanoparticle clusters
<p><strong>meas_00 - meas_09: measurements of particle ensembles</strong></p> <p><strong>meas_10 - meas_11: measurements of excitation beam</strong></p> <p><strong>meas_12: measurement of camera background</strong></p> <p>See "meas_readme.pdf" for more details on how to use and understand the data.</p>
Data from: Chromosome-scale assembly with a phased sex-determining region resolves features of early Z and W chromosome differentiation in a wild octoploid strawberry
<p>Abstract: When sex chromosomes stop recombining, they start to accumulate differences. The sex-limited chromosome (Y or W) especially is expected to degenerate via the loss of nucleotide sequence and the accumulation of repetitive sequences. However, how early signs of degeneration can be detected in a new sex chromosome is still unclear. The sex determining region (SDR) of the octoploid strawberries is young, small, and dynamic. Using PacBio HiFi reads, we obtained a chromosome scale assembly of a female (ZW) <em>Fragaria chiloensis</em> plant carrying the youngest and largest of the known SDR on the W in strawberries. We fully characterized the previously incomplete SDR, confirming its gene content, genomic location and evolutionary history. Resolution of gaps in the previous characterization of the SDR added 10 kbp of sequence including a non-canonical LTR-retrotransposon; whereas the Z sequence revealed a <em>Harbinger</em> transposable element adjoining the SDR insertion site. Limited genetic differentiation of the sex chromosomes coupled with structural variation may indicate an early stage of W degeneration. The sex chromosomes have a similar percentage of repeats but differ in their repeat distribution. Differences in the pattern of repeats (transposable element polymorphism) apparently precede sex chromosome differentiation, thus potentially contributing to recombination cessation as opposed to being a consequence of it.</p> <p>Repository content: data (sequence alignments, phylogenetic trees, genome assembly, and vcf files) and scripts associated with the manuscript "Chromosome-scale assembly with a phased sex-determining region resolves features of early Z and W chromosome differentiation in a wild octoploid strawberry"</p>
Data from: Robust Estimation of Field Inhomogeneity Map Following Magnitude-Based Water-Fat Separation with Resolved Ambiguity
<p>These data have been uploaded and shared as part of "Robust Estimation of Field Inhomogeneity Map Following Magnitude-Based Water-Fat Separation with Resolved Ambiguity". The data may be used for field inhomogeneity mapping and PDFF/R2* reconstruction. </p> <p>These data were acquired by Perspectum Ltd (https://perspectum.com/) on a healthy volunteer. Informed consent was obtained from the participant. The dataset includes a localizer series and a multi-slice series (magnitude and phase) acquired from a volunteer covering the dome of the liver, heart and lungs:</p> <ul> <li>1-localizer_haste_bh</li> <li>2-I_6_Echo_3D_32_Slice_IDEAL</li> <li>3-I_6_Echo_3D_32_Slice_IDEAL</li> </ul> <p>These data were gathered using a Siemens Prisma 3 Tesla scanner. The main dataset comprises an acquisition with thirty-two slices including the abdominal region, with slices placed away from the isocenter. The acquisition consisted of a 6‐echo (TE1=1.3 ms, ΔTE=1 ms) gradient-recalled echo (GRE) protocol designed to minimize T1 bias (3° flip angle), Pixel Bandwidth = 1565 Hz, and 232 x 256 reconstructed image size, with 5 mm slice thickness and 1.72 x 1.72 mm^2 in-plane resolution. </p>
Enabling spectrally resolved single-molecule localization microscopy at high emitter densities: Dataset
<p>The data in this dataset accompanies the various figures present in the publication 'Enabling spectrally resolved single-molecule localization microscopy at high emitter densities'. Contained are tiff files used to create the figures 2-4 and Supplementary figures 1 and 2, as well as csvs after processed with the steps described in the paper (and contained in protocol text files).</p>
Datasets supporting the original submission of Harris et al., "A Global Survey of Rotating Convective Updrafts in the GFDL X-SHiELD 2021 Global Storm Resolving Model"
<p>Datafiles used in the analyses described by Harris et al, "A Global Survey of Rotating Convective Updrafts in the GFDL X-SHiELD 2021 Global Storm Resolving Model", to be submitted to the Journal of Geophysical Research.</p> <p>Model output was created by X-SHiELD 2021 <a href="http://doi.org/10.5281/zenodo.6941034">https://doi.org/10.5281/zenodo.6941034</a> described in the paper:</p> <p>Harris, L., Zhou, L., Lin, S.-J., Chen, J.-H., Chen, X., Gao, K., et al. (2020). GFDL SHiELD: A unified system for weather-to-seasonal prediction. <em>Journal of Advances in Modeling Earth Systems</em>, 12, e2020MS002223.<a href="https://doi.org/10.1029/2020MS002223"> https://doi.org/10.1029/2020MS002223</a></p> <p>GPM data used for Figure 6b is derived from</p> <p>Huffman, G.J., E.F. Stocker, D.T. Bolvin, E.J. Nelkin, Jackson Tan (2019), GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V06, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: 4 August 2021,<a href="https://doi.org/10.5067/GPM/IMERG/3B-HH/06"> 10.5067/GPM/IMERG/3B-HH/06</a></p> <p> </p>
Genome-wide analysis resolves the radiation of New Zealand's freshwater Galaxias vulgaris complex and reveals a candidate species obscured by mitochondrial capture
<p>Aim: Freshwater fish radiations are often characterized by multiple closely-related species in close proximity, which can lead to introgression and associated discordance of mitochondrial and nuclear characterizations of species diversity. As a case in point, single locus nuclear versus mitochondrial analyses of New Zealand's stream-resident <em>Galaxias vulgaris</em> complex have yielded conflicting phylogenies. Our goal is to use genome-wide divergence patterns among these fishes to evaluate the potential role of mitochondrial capture in obscuring species diversity and to understand how ancient and anthropogenic drainage modification explains this diversity.</p> <p>Location: Freshwater ecosystems of New Zealand. Methods: We generate and analyze a genome-wide data set comprising 52,352 SNPs across 187 <em>Galaxias</em> specimens to resolve the phylogeny of this recent fish radiation. We conduct phylogenetic, PCA, STRUCTURE, and ABBA-BABA analyses to evaluate the evolutionary relationships of lineages in the context of natural and anthropogenic river drainage alterations.</p> <p>Results: In addition to the 11 previously recognized stream-resident lineages, genome-wide data reveal a twelfth candidate species (<em>G</em>. 'Pomahaka'), apparently obscured by introgressive mitochondrial capture. We identify additional examples of mito-nuclear discordance and putative mitochondrial capture, likely mediated by geological and anthropogenic modification of drainage boundaries.</p> <p>Main conclusions: Our study highlights the need for genome-wide approaches for delimiting freshwater biodiversity. Genetic data also reveal the influence of drainage history on freshwater biodiversity, including the rapid divergence of recently fragmented fish populations, and the conservation genetic risks of anthropogenic translocations events.</p>
X-ray diffraction images recorded for Aumonier et al., (2022) Slow protein dynamics probed by time-resolved oscillation crystallography at room temperature, IUCrJ
<p>The present repository contains diffraction images corresponding to 27 distinct datasets collected at room temperature on the ESRF beamline ID30A-3 using an Eiger X 4M detector.</p> <p>Datasets have been uploaded with their original names to maintain the metadata integrity. The two following tables match the original names with those attributed in the supplementary table S1 of Aumonier et al., IUCrJ (2022) (https://doi.org/10.1107/S2052252522009150).</p> <table> <tbody> <tr> <td> <p>Data set name on Zenodo</p> </td> <td> <p>X06_01</p> </td> <td> <p>X12_05</p> </td> <td> <p>X07_02_</p> </td> <td> <p>X06_08</p> </td> <td> <p>X14_06</p> </td> <td> <p>X13_03</p> </td> <td> <p>X08_06</p> </td> <td> <p>X11_05</p> </td> <td> <p>X13_05</p> </td> <td> <p>X06_02</p> </td> <td> <p>X11_01</p> </td> <td> <p>X08_01</p> </td> <td> <p>X14_01</p> </td> <td> <p>X13_01</p> </td> <td> <p>X06_03</p> </td> </tr> <tr> <td> <p>Data set in Aumonier et al. 2022</p> </td> <td> <p>Dark</p> </td> <td> <p>PS2</p> </td> <td> <p>PS2</p> </td> <td> <p>PS3</p> </td> <td> <p>PS4</p> </td> <td> <p>PS5</p> </td> <td> <p>PS6</p> </td> <td> <p>PS7</p> </td> <td> <p>R<sub>2”</sub></p> </td> <td> <p>R<sub>3”</sub></p> </td> <td> <p>R<sub>7”</sub></p> </td> <td> <p>R<sub>10”</sub></p> </td> <td> <p>R<sub>13”</sub></p> </td> <td> <p>R<sub>21”</sub></p> </td> <td> <p>R<sub>35”</sub></p> </td> </tr> </tbody> </table> <p> </p> <table> <tbody> <tr> <td> <p>Data set on Zenodo</p> </td> <td> <p>X08_02</p> </td> <td> <p>X11_02</p> </td> <td> <p>X12_02</p> </td> <td> <p>X14_02</p> </td> <td> <p>X13_04</p> </td> <td> <p>X13_02</p> </td> <td> <p>X12_06</p> </td> <td> <p>X06_09</p> </td> <td> <p>X09_04</p> </td> <td> <p>X12_04</p> </td> <td> <p>X06_07</p> </td> <td> <p>X13_07</p> </td> </tr> <tr> <td> <p>Data set in Aumonier et al. 2022</p> </td> <td> <p>R<sub>51”</sub></p> </td> <td> <p>R<sub>62”</sub></p> </td> <td> <p>R<sub>62”</sub></p> </td> <td> <p>R<sub>67”</sub></p> </td> <td> <p>R<sub>72”</sub></p> </td> <td> <p>R<sub>80”</sub></p> </td> <td> <p>R<sub>90”</sub></p> </td> <td> <p>R<sub>130”</sub></p> </td> <td> <p>R<sub>166”</sub></p> </td> <td> <p>R<sub>258”</sub></p> </td> <td> <p>R<sub>630”</sub></p> </td> <td> <p>R<sub>1620”</sub></p> </td> </tr> </tbody> </table> <p>One dataset consists of a master file, four data files and two metadata files.</p>
Data and code for Coherent Correlation Imaging: Resolving fluctuating states of matter
<p>Data and code to generate the figures in the main text and the Extended data figures.</p>
Datasets for "Resolving the microscopic hydrodynamics at the moving contact line"
<p>Datasets for the article:</p> <p>"Resolving the microscopic hydrodynamics at the moving contact line" <br> Amal K. Giri, Paolo Malgaretti, Dirk Peschka, and Marcello Sega<br> Phys. Rev. Fluids <strong>7</strong>, L102001<br> DOI: 10.1103/PhysRevFluids.7.L102001</p> <p>Includes:</p> <ol> <li>GROMACS input files</li> <li>Modifications to the GROMACS source code thermostat as described in the article</li> <li>Instructions on how to invoke the patched version of GROMACS with decoupled directions</li> <li>Matlab datafiles with FE solutions and scripts to analyse and compare them to MD velocity field (also included)</li> </ol> <p> </p> <p>See also: <br> https://github.com/Marcello-Sega/pytim<br> https://github.com/dpeschka/stokes-free-boundary</p>
Data from: Bratzel et al. (2022) Target-enrichment sequencing reveals for the first time a well-resolved phylogeny of the core Bromelioideae (Bromeliaceae). Taxon
<p>DNA sequence alignments used for phylogenetic analyses in Bratzel et al. (2022) Target-enrichment sequencing reveals for the first time a well-resolved phylogeny of the core Bromelioideae (Bromeliaceae). Taxon.</p>
A method to determine local aerodynamic force coefficients from fiber-resolved 3D flow simulations around a staple fiber yarn: simulation data
<p>This data set contains all set-up files and necessary scripts to run the simulations performed in the publication <a href="https://doi.org/10.1007/s11044-024-09992-2" target="_blank" rel="noopener">"A method to determine local aerodynamic force coefficients from fiber-resolved 3D flow simulations around a staple fiber yarn"</a>, published in Multibody System Dynamics.</p>
Dataset for the paper "Accelerating Seafloor Uplift of Submarine Caldera near Sofugan Volcano, Japan, Resolved by Distant Tsunami Recordings"
<p>The results of the analysis in the paper "Accelerating Seafloor Uplift of Submarine Caldera near Sofugan Volcano, Japan, Resolved by Distant Tsunami Recordings" published in Geophysical Research Letters are available here. For the details of the file, please see Readme.pdf.</p>
Dataset of 4D conserved tracers for convection simulated by large eddy model and cloud resolving model
<p>There are conserved tracers and active flag for convection used for diagnosis of bulk entrainment rate for four convection cases in this dataset. Total water and moist static energy are selected as tracer for shallow convection (BOMEX and RICO) and deep convection (GATE and KWAJEX), respectively. The two variables simulated by large eddy model for shallow convection and cloud resolving model for deep convection are four-dimension variables with horizontal scales, vertical altitude, and time. </p> <p>The size of domain simulated for BOMEX and RICO is 6.4 km with horizontal grid spacing of 100 m, and that GATE and KWAJEX is 256 km with horizontal grid spacing of 1 km. Besides, vertical layers in the simulation are 75 levels with spacing of 40m for BOMEX and 100 levels with spacing of 40m for RICO. For KWAJEX and GATE, the model was set up with 64 levels vertically, which gradually increases from 75 m at the surface to a spacing of 400 m through the troposphere and a larger spacing of 1 km in the Newtonian damping region. The model is integrated for 6 hours for BOMEX, 24 hours for RICO, 52.25 days for KWAJEX, and 20 days for GATE. Here, the range of time in these variables The four-dimension variables are saved every 3 seconds for shallow convection, and every 6 minutes for deep convection for two consecutive days.</p>
Figure 36 in Recognising variability in the shells of argonauts (Cephalopoda: Argonautidae): the key to resolving the taxonomy of the family
Figure 36. Images of live female argonauts, Argonauta hians and A. nodosus, demonstrating the effect of spawned eggs on the position of the females relative to their shells: a, live female A. hians from Andaman Sea, Thailand, photographed in an aquarium (photo: J. Nabhitabhata, after Sukhsangchan and Nabhitabhata 2007); b–c, A. nodosus Phillip Bay, Victoria, Australia (photos: R. Kuiter); b, live female argonaut photographed in the wild; c, eggs of same specimen, shown with argonaut removed from shell.
Figure 35. Preserved female Argonauta nouryi and A in Recognising variability in the shells of argonauts (Cephalopoda: Argonautidae): the key to resolving the taxonomy of the family
Figure 35. Preserved female Argonauta nouryi and A. hians with spawned eggs: a, preserved female A. nouryi from the Pacific Ocean (15.2 mm dorsal mantel length, 18.4 mm shell length, SBMNH 64369) with spawned eggs attached to the axis of the shell; b, preserved female A. hians from the North West Shelf, Western Australia (28.7 mm dorsal mantel length, 38.9 mm shell length, QM Mo77789) with yellow eggs visible in dorsal component of shell. Scale bar = 1 cm.
Figure 33. Repaired Argonauta argo shell from Monterey, California. Repaired A in Recognising variability in the shells of argonauts (Cephalopoda: Argonautidae): the key to resolving the taxonomy of the family
Figure 33. Repaired Argonauta argo shell from Monterey, California. Repaired A. argo shell from Monterey, California (81.9 mm shell length, USNM 61374): a, left lateral view; b, oblique left lateral view; c, oblique anterior aperture view. Note change in direction of lateral ribs along repair line. Scale bar = 1 cm.
Figure 32 in Recognising variability in the shells of argonauts (Cephalopoda: Argonautidae): the key to resolving the taxonomy of the family
Figure 32. Coarse and fine Argonauta argo shells: a–b, shells of A. argo displaying different degree of sculpturing and variation in the aperture edge; a, fine A. argo shell from off San Clement Island, California (113.3 mm shell length [P], USNM 316580); b, coarse A. argo shell from Baja California (128.1 mm shell length [P], ANSP 404279). Scale bar = 1 cm.
Figure 31 in Recognising variability in the shells of argonauts (Cephalopoda: Argonautidae): the key to resolving the taxonomy of the family
Figure 31. Single eared Argonauta nodosus shell from the British Museum: a–c, three perspectives of a single eared A. nodosus shell from the British Museum (109.0 mm shell length [P], BMNH unreg., locality unknown, "B395, e."); a, left lateral view; b, right lateral view; c, anterior aperture view. Scale bar = 1 cm.
Figure 29 in Recognising variability in the shells of argonauts (Cephalopoda: Argonautidae): the key to resolving the taxonomy of the family
Figure 29. Coarse and fine Argonauta nodosus shells: a, fine A. nodosus shell from Mayor Is., Bay of Plenty, New Zealand (127.2 mm shell length, NMV F164784); b, Coarse A. nodosus shell from the Indo Pacific (127.3 mm shell length, NMV F164774). Scale bar = 1 cm.
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.