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3,655 results for “Structural data”
Fig. 9 in Species authentication of Tor spp. (family Cyprinidae) in Indonesia based on osteocranium structure and biometric data
Fig. 9. Multivariate analysis (PCA) of the osteocranium biometric characters of four Tor species.
Expansion of the RNAStructuromeDB to include secondary structural data spanning the human protein-coding transcriptome
<p>This dataset includes the -2, -1, and no filter z-score dot bracket files from ScanFold for all protein coding transcript isoforms.</p>
Raw NMR data for Structural Studies of Alloyed and Nanoparticulate Transition Metal Dichalcogenides by Selenium-77 Solid-State Nuclear Magnetic Resonance Spectroscopy
<p>Raw NMR data for main text figures.</p>
Wikidata: the potential of structured data to enable applications such as Histropedia
<p>Despite the vast number of uses for Wikipedia, you still can’t ask it even simple questions like “who is the Mayor of London?” – Computers simply do not understand the unstructured data. Wikidata is a ground-breaking new Wikimedia project that aims to tackle this problem and many others, by making the sum of all human knowledge machine-readable. It will provide a<br>back end to Wikipedia, potentially allowing a single change in Wikidata to correct and improve information represented in multiple places in Wikipedia, across all language versions.<br>In this presentation I will give a basic overview of how Wikidata works, including information about how the data is structured and connected to other resources on the internet, as well as the methods being used to collect and organize the data. I will also highlight the major similarities and differences between Wikidata and the already widely used DBpedia.Finally, I will go on to explain the implications of Wikidata’s development for the future of Wikipedia and the rest of the web, giving examples of applications that have already been built upon data from Wikidata such as Histropedia, which aims to visualize the sum of all knowledge using interactive timelines.</p>
Supplementary data to BANMF-S: a blockwise accelerated non-negative matrix factorization framework with structural network constraints for single cell RNA-seq data imputation
Open the record for dataset details and reuse information.
Data to accompany Structural prediction of chimeric immunogens to elicit targeted antibodies against betacoronaviruses
<p>This dataset contains predicted chimera structures, NanoDSF data on thermal stability of expressed chimeras on the surface of pseudoviruses, and immunofluorescence data on expressed chimeras on the surface of pseudoviruses as described in the manuscript.</p>
Data for: Food Web Structure Significantly Affects the Body Condition and Survival of an Amphibian Intraguild Predator
<p>Data for upcoming publication</p>
Data from: Ambient noise tomography of upper crustal structures and Quaternary faults in the Seoul metropolitan area and its geological implications
<p class="0"><span><span><span>We investigate the upper-crustal seismic velocity structure in the Seoul metropolitan</span> <span>area, where about 20 million people live. The Chugaryeong fault zone (CFZ) is</span> <span>placed in this area, but the seismic hazard potential remains unclear. We conducted</span> <span>ambient noise tomography to illuminate the high-resolution upper-crustal structure</span> <span>in the Seoul metropolitan area. We analyzed continuous vertical seismic records</span> <span>for ~5 months from a dense seismic array with 77 broadband stations. Group</span> <span>velocity dispersion curves and tomographic maps were extracted between 0.5 and 10</span> <span>s periods. We inverted 3-D group velocity tomography models up to a depth of ~10</span> <span>km from the group velocity maps. The shear-wave velocity model is consistent with</span> <span>the geological features. High-velocity anomalies at shallow depths are correlated</span> <span>with the surface topography and geology. The CFZ is located at a low velocity below the 5 km depth and presented as the simplified model. The large </span><span>V</span><span><sub>S</sub> </span><span>contrast</span> <span>regions are located beneath NS-trending faults. The cross-sections coincide with</span> <span>the near-vertical strike-slip faults in this area. In the southern region of the Seoul</span> <span>metropolitan area, low-velocity anomalies correlate with high heat flow regions. Our</span> <span>results effectively suggest high resolution upper-crustal structures and subsurface</span> <span>hidden faults in the urban area.</span></span></span></p>
Data set for "Investigating the structural changes due to adenosine methylation of ORF50 in Kaposi's sarcoma-associated herpes virus"
<p>Data set containing the pathsample databases, and analysis scripts used</p>
Raw diffraction data for structure of SARS-CoV-2 main protease with ABT-957 (PDB: 7QT8)
<p>Raw diffraction data for SARS-CoV-2 main protease in complex with ABT-957 collected as part of an room-temperature crystallographic ligand screening experiments on beamline i24 at Diamond Light Source.</p>
Data from: Spatial familial networks to infer demographic structure of wild populations
<p class="List1">In social species, reproductive success and rates of dispersal vary among individuals resulting in spatially structured populations. Network analyses of familial relationships may provide insights on how these parameters influence population-level demographic patterns. These methods have however rarely been applied to genetically-derived pedigree data from wild populations.</p> <p class="List1">Here we use parent-offspring relationships to construct familial networks from polygamous boreal woodland caribou (<i>Rangifer tarandus caribou</i>) in Saskatchewan, Canada, to inform recovery efforts. We collected samples from 933 individuals at 15 variable microsatellite loci along with caribou-specific primers for sex identification. Using network measures, we assess the contribution of individual caribou to the population with several centrality measures and then determine which measures are best suited to inform on the population demographic structure. We investigate the centrality of individuals from eighteen different local areas, along with the entire population.</p> <p class="List1">We found substantial differences in centrality of individuals in different local areas, that in turn contributed differently to the full network, highlighting the importance of analyzing networks at different scales. The full network revealed that boreal caribou in Saskatchewan form a complex, interconnected familial network, as the removal of edges with high betweenness did not result in distinct subgroups. Alpha, betweenness, and eccentricity centrality were the most informative measures to characterize the population demographic structure and for spatially identifying areas of highest fitness levels and family cohesion across the range. We found varied levels of dispersal, fitness and cohesion in family groups.</p> <p class="List1"><i>Synthesis and applications</i>: Our results demonstrate the value of different network measures in assessing genetically-derived familial networks. The spatial application of the familial networks identified individuals presenting different fitness levels, short and long-distance dispersing ability across the range in support of population monitoring and recovery efforts.</p>
Data From: Getting cited early: influence of visibility strategies, structure, and focal system on early citation rates
<p>Elucidating factors that contribute to citation rates of scientific articles can help scientists write manuscripts that have a stronger influence on their scientific field and wildlife management, and are accessible to a broad audience. Using a cohort of 778 articles published in <i>The Journal of Wildlife Management</i> from 2011–2015, we examined how visibility strategies (e.g., open access, increasing the Atlmetric Attention Score, self-citations), article structure, and focal system – all factors authors can predominantly control – influenced the accumulation of citations over various time frames within the first 5 years after publication, and the number of days until an article received its first citation. Visibility strategies influenced the number of citations accrued within the first year following publication. Our model explained less of the variation in number of citations received 1 year post-publication compared to 5 years post-publication (R<sup>2</sup> increased from 0.12 to 0.57 from years 1 to 5). Two years post-publication, factors associated with an article's visibility increased citation counts, and factors associated with article structure and focal system became important. Our analyses suggest citation rates, within wildlife ecology, are influenced by a number of controllable factors and that the influence of an article on science and management can be increased by authors pursuing a variety of visibility strategies.</p>
Data from: Anderson lab experiments from synthesizing the effects of spatial network structure on predator prey dynamics
<p>Predator-prey persistence is thought to be enhanced by spatial heterogeneity. Theory predicts that metacommunity size, spatial connectivity, network synchrony, predator identity, and productivity influence predator-prey persistence, through a variety of mechanisms such as statistical stabilization, colonization-extinction dynamics, and trophic interactions. However, comparative tests and synthesis of the multiple factors and mechanisms across different spatial networks are needed to understand which factors and mechanisms of spatial network structure promote predator-prey persistence. To address this gap between theory and empirical work, we synthesized data from 22 microcosm experiments of protist predator-prey communities differing the productivity, connectivity, and size of spatial habitat structure. Prey time to extinction was better explained by productivity and spatial factors than predator time to extinction. At the local and regional scale, metacommunity size and productivity had positive effects on prey occupancy, whereas connectivity negatively influenced prey occupancy. For predators, metacommunity size and connectivity had positive effects on predator occupancy, network synchrony had negative influences, and productivity showed a hump-shaped relationship with predator occupancy. Further, trophic interactions drove variation in the way species were spatially structured, where the strength and direction of predator and prey occupancy relationships varied among productivity levels and predator-prey combinations. In predator-prey interactions that were stronger, prey occupancy showed negative relationship with predator occupancy regardless of productivity. However, in predator-prey interactions that were weaker, prey occupancy was positively related to predator occupancy at low productivity, and this relationship disappeared at higher productivity treatments where prey occupancy was high regardless of predator occupancy. Predictions from metapopulation theory explained predator occupancy, while prey were better explained by trophic dynamics. Taken together, these results highlight that spatial network structure has a complex, spatially contingent relationship with predator-prey dynamics.</p>
Data cubes corresponding to the article "Three-dimensional Structure of the Corona during WHPI Campaign Rotations CR-2219 and CR-2223"
<p>CONTENTS of REPOSITORY:</p> <p>The shared data corresponds to 3D tomographic reconstructions and 3D MHD simulations of the solar corona and solar wind of WHPI targets CR-2219 and CR-2223. Each 3D cube of data is specified in a uniform spherical grid, as described in the IDL codes that allow reading the cubes into memory. The specific shared products are: </p> <p>3D Tomographic reconstructions:<br> * DEMT: Electron density (Ne) and temperature (Te) in the height range 1.02-1.25 Rsun (based on AIA images).<br> * WL-SRT: Electron density (Ne) in the height range 2.5-6.0 Rsun (based on LASCO-C2 data). </p> <p>3D MHD steady-state simulations using the AWSoM model:<br> * Electron density (Ne) and temperature (Te).<br> * Magnetic field components (Br, Bth, Bph).<br> * Radial component of the solar wind velocity (Vr).</p> <p>INSTRUCTIONS: The IDL script included contains comments describing how to read into memory the data.<br> </p>
Structural conversion of α-synuclein at the mitochondria induces neuronal toxicity; Data sets
<p>Lists of data sets included in <strong>"Structural conversion of α-synuclein at the mitochondria induces neuronal toxicity"</strong></p> <p> </p> <p>Single-molecule confocal Quantification_Images (SNCA-A53T TIRF Images)</p> <p>TIRF Image Quantification</p> <p>TIRF Emission Data</p> <p>Single Vesicle Emission Data</p> <p>DLS Emission Data</p> <p>CD Measurements</p> <p>Amyloid Fibril TIRFM Emission Data </p> <p>α-Syn WT, A53T, A30P and E46K Confirmatory LCMS </p> <p>SNCA A53T iPSC mutation confirmatory Sanger Sequencing</p> <p>ELISA</p> <p>Immunocytochemistry (MAP2 and TRB1)</p> <p>Pierce BCA Protein Assay</p> <p>Aggregation Assay</p> <p>Copy of Empiar_upload_info (CLEM quantification); metadata spreadsheet for TEM and FIB-SEM Image Quantification</p> <p>Live-cell imaging data</p> <ul> <li>Superoxide Emission Data</li> <li>MitoTracker® Red Emission Data</li> <li>MembranePotentialEmissionData (the same experiment for ' TMRM Emission data')</li> <li>Ca 2+ Emission Data</li> <li>NADH Autofluorescence and Redox Quantification</li> <li>ATP Emission Data</li> <li>mPTP Emission Data</li> <li>Cell Death Emission Data (PI & SYTOX)</li> <li>FRET Emission Data</li> <li>MitoTracker® Red Assay</li> <li>Cell Death Assay</li> </ul>
Haplotype-phasing of long-read HiFi data to enhance structural variant detection through a Skip-Gram model
<p>Example dataset for DipPAV</p>
Original data for "Multiple co-existing structures of an RNA four-way junction resolved by FRET, SAXS, and integrative modeling"
<p>Experimental single-molecule FRET data (Intensity ratio histograms) and starting structures used for rigid body docking for an RNA four-way junction related to the hairpin ribozyme.</p> <p> </p>
Data from: Cultural transmission of tool use combined with habitat specializations leads to fine-scale genetic structure in bottlenose dolphins
[No abstract entered]
Data from: Contrasting responses in community structure and phenology of migratory and non-migratory pollinators to urbanization
[No abstract entered]
Data from: Genetic structure of the white-footed mouse in the context of the emergence of Lyme disease in southern Québec
[No abstract entered]
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.