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199 results for “correlation analysis”
Dynamic X-ray CT of Synthetic magma for Digital Volume Correlation analysis
<p>Dataset of synthetic magma subjected to compression, useful for Digital Volume Correlation analysis, ref [1,2]. The data has been acquired at the Diamond Light Source synchrotron, with a bespoke thermo-mechanical rig (“P2R”) on the I12 beamline, ref [3,4,5]. Dataset 0 has no applied compression, while dataset 1 has applied compression.</p> <p>The data was saved with numpy 1.21 with <a href="https://numpy.org/doc/1.21/reference/generated/numpy.lib.format.html#format-version-1-0">NumPy format version 1.0</a> as dataset_0.npy and dataset_1.npy, and NumPy can be used to read it back in. Both data files have a header specifying how the data is stored, and following the header comes the array data.</p> <p>In particular the header length is 128 bytes, and the data consists of a 3 dimensional matrix of size (1520, 1257, 1260) stored in unsigned integer 8 bit, Fortran order. The screenshot named import_imagej.png shows how to import the data in with <a href="https://imagej.nih.gov/ij/">ImageJ</a>.</p> <p> </p> <p>A <a href="https://github.com/Kitware/MetaIO">METAImage</a> header describing the data in text form for each dataset is also provided, i.e. dataset_0.mhd and dataset_1.mhd,</p>
Analysis of correlation-based biomolecular networks from different omics data by fitting stochastic block models
<p><strong>Baum_et_al_2019_Supplementary_Figures.pdf: </strong>Supplementary Figures S1-S4. Legends are included under each figure.</p> <p><strong>sbm-for-correlation-based-networks-master.zip: </strong>Archived source code of R and Python functions for the analyses and example workflow description at time of publication. Files are maintained at https://gitlab.com/biomodlih/sbm-for-correlation-based-networks and https://gitlab.com/kabaum/sbm-for-correlation-based-networks.</p>
Data For Scalco et al. Clinicopathological correlates of quantitative Amyloid-B Pathology in the Temporal Cortex: Machine learning analysis of 131 cases from an ADRC
<p>Dataset containing 131 de-identified whole slide images (WSIs) with a respective data dictionary. </p> <p><strong>Paper</strong>: Scalco, R., Oliveira, L.C., Lai, Z. et al. Machine learning quantification of Amyloid-β deposits in the temporal lobe of 131 brain bank cases. acta neuropathol commun 12, 134 (2024). https://doi.org/10.1186/s40478-024-01827-7</p> <p><strong>Details</strong>: A total of 131 .svs. WSIs, de-identified using svs-deidentifier v 0.9.1-beta (https://github.com/pearcetm/svs-deidentifier/releases). Dataset is uploaded in batches due to Zenodo data upload limitations.</p> <p><strong>Slide curation/preparation</strong>: All samples were retrieved from archives of the University of California, Davis Alzheimer’s Disease Center Brain Bank (<a href="https://www.ucdmc.ucdavis.edu/alzheimers/">https://www.ucdmc.ucdavis.edu/alzheimers/</a>). Archival samples analyzed in this study were 5 μm formalin fixed, paraffin embedded sections of the superior and middle temporal gyrus from human brain. The tissue had been previously stained with an amyloid-β antibody (4G8, recognizing residues 17-24, BioLegend, formerly Covance) that were first pretreated with formic acid to rid samples of endogenous protein. All slides were digitized using an Aperio AT2 between 20x and 40x magnification.</p> <p><strong>Code:</strong> Please refer to <a href="https://github.com/ucdrubinet/BrainSec">https://github.com/ucdrubinet/BrainSec</a> and <a href="https://github.com/keiserlab/plaquebox-paper">https://github.com/keiserlab/plaquebox-paper</a></p>
Characteristic and spatiotemporal variation of air pollution in Northern China based on correlation analysis and clustering analysis of five air pollutants
<p>original daily data for 'Characteristic and spatiotemporal variation of air pollution in Northern China based on correlation analysis and clustering analysis of five air pollutants'</p>
Integrating differential expression and weighted correlation network analysis for identifying genes controlling shoot development in Sorghum bicolor
<p>Supplementery materials of journal article "Integrating differential expression and weighted correlation network analysis for identifying genes controlling shoot development in <em>Sorghum bicolor</em>"</p>
Рис. 5. АналиЗ линейной коррелЯции параметров макробентоса от доминируюЩей фракции в пробе грунта (А, Б) и глубины (В, Г). Fig. 5. Analysis of the linear correlation of macrobenthos parameters with the dominant fraction in the bottom sample (А, Б) and depth (В, Г). in Species composition and distribution of bivalve mollusks in plankton and benthos in Nevelsky Strait in summer
Рис. 5. АналиЗ линейной коррелЯции параметров макробентоса от доминируюЩей фракции в пробе грунта (А, Б) и глубины (В, Г). Fig. 5. Analysis of the linear correlation of macrobenthos parameters with the dominant fraction in the bottom sample (А, Б) and depth (В, Г).
Fig. 3 in The correlations between certain features of the journal Neotropical Ichthyology and its impact factor: a comparative analysis at the thematic and national levels
Fig. 3. Correlation between average IF and uncitedness rate of journals on zoology in Sample 1 between 2006 and 2010. The highlighted represents the data for Neotropical Ichthyology.
Fig. 3 Canonical correspondence analysis. Only axes 1 and 2 are shown. Type 2 in Evaluating the correlation between area, environmental heterogeneity, and species richness using terrestrial isopods (Oniscidea) from the Pontine Islands (West Mediterranean)
Fig. 3 Canonical correspondence analysis. Only axes 1 and 2 are shown. Type 2 scaling is shown. A right-angled projection of a point representing a response variable (ecological categories of species) onto an arrow representing an explanatory variable (biotope type)
Data for: "A high-throughput microscopy method for single-cell analysis of event-time correlations in nanoparticle-induced cell death"
<p>Data related to the publication Murschhauser <em>et al.</em>: <a href="https://doi.org/10.1038/s42003-019-0282-0">A high-throughput microscopy method for single-cell analysis of event-time correlations in nanoparticle-induced cell death</a>. It contains fluorescence time traces of single cells marked with cell-event markers and observed by time-lapse microscopy. The cells were treated with nanoparticles at different doses (NP25 and NP100), with staurosporine (sts) or were left untreated for control (ctrl). See the above-mentioned publication for more details.</p> <p>The format of the data is described below.</p> <p>The file <code>Data_A549.zip</code> contains data measured with A549 cells, and the file <code>Data_Huh7.zip</code> contains data measured with Huh7 cells. Both files have the same structure. Each file contains the directories <code>Raw</code> and <code>Fitted</code> as well as a checksum file. The <code>Raw</code> directory contains single-cell fluorescence time courses as obtained by time-lapse microscopy. The <code>Fitted</code> directory contains the results of fitting model functions as well as properties of identified events, such as event times. The checksum file contains SHA256 checksums of all files within these directories and can be used to check file integrity.</p> <p>Both directories contain measurement directories. Each measurement directory contains the data corresponding to one experiment. The name of the measurement directory is the measurement identifier. Each measurement directory contains condition directories. Each condition directory contains data corresponding to one condition measured in the measurement and is named after the condition. Each condition directory contains marker directories. They are named after the fluorescence markers measured and contain files with single-cell data corresponding to the respective markers.</p> <p>The names of those files consist of multiple parts separated by underscores. The first two parts identify a position of the microscope. Since pairs of markers were measured, each position is present in two marker directories. The third part is the measurement identifier. The other parts will be described below.</p> <p>The <code>Raw</code> directory contains only CSV files with the raw fluorescence time courses. The filenames contain no other parts and have the suffix “.txt”. The first row of each CSV file is the time (in units of 10 minutes), and the other rows are the fluorescence time courses of the cells observed at the corresponding position (in arbitrary units). Each file in the <code>Raw</code> directory corresponds to a group of files in the <code>Fitted</code> directory.</p> <p>The <code>Fitted</code> directory contains three types of CSV files. Their names have “ALL” as fourth part, a session identifier as sixth part and the suffix “.csv”. The fifth part indicates the type of file and is one of the following:</p> <ul> <li>“PARAMS” indicates the estimated values for the model parameters. Each row stands for one cell and each column for a parameter of the model function fitted to the data. The model functions are published with the <a href="https://doi.org/10.5281/zenodo.1418465">fitting software</a>.</li> <li>“SIMULATED” indicates the fitted traces. The traces are calculated using the model functions and the estimated parameters. The format is the same as for the raw traces, but the time is in units of hours and has a higher resolution.</li> <li>“STATE” indicates additional information extracted from the fitted traces. Each row stands for a cell and each column for a property. The first column is the number of the cell. The second column is the event time found (in hours); non-finite values indicate that no event time was found. The third and fourth columns contain the absolute and relative amplitude of the trace, respectively. The fifth column is the logarithmic likelihood of the best fit. The sixth column indicates an algorithm used for postprocessing, and the seventh column indicates the trace slope at the event. See the fitting software for details.</li> </ul> <p> </p>
Figure. Constrained ordination plot as produced from canonical correspondence analysis (CCA). The variability of environmental variables is summarized on Axis 1 and Axis 2 of the constrained biplot, explaining the variability of the trophic groups included in the red fox's diet. Trophic groups are shown with black line (unfilled) pyramids, whereas environmental variables are shown with black filled pyramids. Proximity and distance of response centroids to predictor centroids indicate positive and negative correlations between them, respectively. in Factors affecting the diet of the red fox (Vulpes vulpes) in a heterogeneous Mediterranean landscape
Figure. Constrained ordination plot as produced from canonical correspondence analysis (CCA). The variability of environmental variables is summarized on Axis 1 and Axis 2 of the constrained biplot, explaining the variability of the trophic groups included in the red fox's diet. Trophic groups are shown with black line (unfilled) pyramids, whereas environmental variables are shown with black filled pyramids. Proximity and distance of response centroids to predictor centroids indicate positive and negative correlations between them, respectively.
Analysis of correlation between water pollution in Höfen and Covid-19 cases in Austria, in 2020 dataset
<p>Dataset about water pollution in Höfen and COVID-19 cases in Austria, in 2020. The measured water pollution corresponds to the daily COVID-19 cases and deaths.</p>
Adopted Ranking Methodology for Emerging National Importance Technical Institutions: A Correlation Analysis and Dominance of Research Performance Indicators
<p>The article presents the research performance of newly established technical institutes in India. It gives an overview of NTU and NIRF ranking methodologies. This research would help institutions to check their performance and identify ways to strengthen their rank by producing more output with high-impact research work. The article provides appropriate input to the technical institutions under the study to set out practical and pedagogical approaches, and cross-institutional as well as international collaboration to achieve their research goals. The article gives rank to the technical institutes under the study based on their research performance using the NTU ranking methodology.</p>
Correlation of native and exotic species richness: a global meta-analysis finds no invasion paradox across scales
This data set is also available on the Dryad Digital repository (link : https://doi.org/10.5061/dryad.59kv753) This dataset was created for investigating the biotic resistance hypothesis, that is, the idea that species‐rich communities are more successful at resisting invasion by exotic species than are species‐poor communities. It has been argued that native–exotic richness relationships (NERR) are negative at small spatial scales and positive at large scales, but evidence for the role of spatial scale on NERR has been contradictory. However, no formal quantitative synthesis had previously examined whether NERR is scale‐dependent across multiple studies, and previous studies on NERR have not distinguished spatial grain and extent, which may drive very different ecological processes Therefore, a global systematic review was carried out to create this dataset, which includes 204 individual cases of observational (non‐experimental) NERRs from 101 publications. Further, the above-mentioned hypotheses were investigated using a hierarchical mixed‐effects meta‐analysis, which showed that NERR was indeed highly scale dependent across studies and increased with the log of grain size. Also, no clear patterns of NERR across different spatial extents were found, suggesting that extent plays a less important role in determining NERR than does grain, although there was a complex interaction between extent and grain size. Almost all studies on NERR were found to have been conducted in North America, western Europe, and a few other regions, with little information on tropical or Arctic regions. NERR was also found to increase northward in temperate regions and vary with longitude. These results were published in the paper titled Correlation of native and exotic species richness: a global meta‐analysis finds no invasion paradox across scales (Peng et al. 2018), which represents the first global quantitative analysis of scale‐based NERR.
Characteristic and spatiotemporal variation of air pollution in Northern China based on correlation analysis and clustering analysis of five air pollutants
<p>Data for "Characteristic and spatiotemporal variation of air pollution in Northern China based on correlation analysis and clustering analysis of five air pollutants"</p>
Data in the analysis of Comparative Study of the Impact of Dummy Variables on Regression Coefficients and Canonical Correlation Indices: an Empirical perspective
<p>This data is used in the analysis related to the article Comparative Study of the Impact of Dummy Variables on Regression Coefficients and Canonical Correlation Indices: an Empirical perspective. The data contain Crude Oil Prices, Exchange Rates, and Dummy variables coded 1 for the era before the Covid-19 outbreak and 0 for the era of Covid-19.</p> <p> </p>
Data from: Comparative analysis of the shape and size of the middle ear cavity of turtles reveals no correlation with habitat ecology
<p>The middle ear of turtles differs from other reptiles in being separated into two distinct compartments. Several ideas have been proposed as to why the middle ear is compartmentalized in turtles, most suggesting a relationship with underwater hearing. Extant turtle species span fully marine to strictly terrestrial habitats, and ecomorphological hypotheses of turtle hearing predict that this should correlate with variation in the structure of the middle ear due to differences in the fluid properties of water and air. We investigate the shape and size of the air-filled middle ear cavity of 56 extant turtles using 3D data and phylogenetic comparative analysis to test for correlations between habitat preferences and the shape and size of the middle ear cavity. Only weak correlations are found between middle ear cavity size and ecology, with aquatic taxa having proportionally smaller cavity volumes. The middle ear cavity of turtles exhibits high shape diversity among species, but we found no relationship between this shape variation and ecology. Surprisingly, the estimated acoustic transformer ratio, a key functional parameter of impedance-matching ears in vertebrates, also shows no relation to habitat preferences (aquatic/terrestrial) in turtles. We suggest that middle ear cavity shape may be controlled by factors unrelated to hearing, such as the spatial demands of surrounding cranial structures. A review of the fossil record suggests that the modern turtle ear evolved during the Early to Middle Jurassic in stem turtles broadly adapted to freshwater and terrestrial settings. This, combined with our finding that evolutionary transitions between habitats caused only weak evolutionary changes in middle ear structure, suggests that tympanic hearing in turtles evolved as a compromise between subaerial and underwater hearing.</p>
RAW data for Correlation analysis of vibration modes in physical vapour deposited Bi2Se3 thin films probed by the Raman mapping technique
<p>Raw data for the "Correlation analysis of vibration modes in physical vapour deposited Bi2Se3 thin films probed by the Raman mapping technique" paper.</p>
Inappropriate rightward saccades after right hemisphere damage: Oculomotor analysis and anatomical correlates
<p>Patients with right hemisphere damage and visual neglect have severe problems to orient attention towards left-sided objects, often associated with the tendency to produce inappropriate rightward saccades. In its most severe form, this tendency can assume the compulsive character of a rightward deviation of gaze as soon as the visual scene deploys (so-called “magnetic attraction of gaze”). However, little is known about the exact nature of inappropriate rightward saccades, their relation with impaired conscious perception of left-sided stimuli, and their lesional correlates. To explore these issues, we studied three groups of patients with right brain damage: patients with signs of left visual neglect associated to left homonymous hemianopia, neglect patients without hemianopia, and patients without neglect or hemianopia. Participants searched for a gap missing within a target, presented among distractors. Manual responses for target detection were required, while participants were encouraged to move their eyes during search. Endogenous attention could be summoned to the target location by a central cue. All the three groups of patients produced inappropriate rightward saccades, which could not be completely overcome by the endogenous orienting of attention induced by the cues. Anatomical analysis indicated a specific implication of damage to the right frontal eye field and to a long-range white matter tract, the fronto-parietal superior longitudinal fasciculus. Fronto-parietal networks in the right hemisphere appear thus to be essential to integrate covert and overt orienting of attention, and to thoroughly explore space in order to become aware of the multiple competing objects around us.</p>
Correlation-based Analysis of the Influence of Bound Constraint Handling Methods on Population Dynamics in Differential Evolution
<p>The dataset is based on the average values collected over 5 independent runs, considering the largest common number of<br>iterations for LSHADE algorithm coupled with ’sat’, ’midT’, ’midB’, ’unif’, ’beta’, ’mir’, ’tor’, ’expC_R’, ’expC_T’, ’expC_B’, ’vectR’, ’vectT’, ’vectB’, ’mahalanobis’ correction methods, on BBOB function f3, 4, 5, 16, 23, instance 1</p> <p>Plots for the averaged values are included for measures 'pop_size', 'best', 'error', 'prob_infeas', 'genMutatedComponent', 'genSuccessMutants','meanImprovements', 'varPop', 'avgF', 'avgCR', 'extension', 'shape', 'eccentricity', 'kl_unif'</p>
Replication Package for "On the correlation between Architectural Smells and Static Analysis Warnings"
<div> <div> <div> <div> <div> <h1>Replication Package for the Paper: "On the Relation between Architectural Smells and Static Analysis Warnings"</h1> <h2>Authors</h2> <ul> <li>Matteo Esposito, University of Oulu, Finland</li> <li>Mikel Robredo, University of Oulu, Finland</li> <li>Francesca Arcelli Fontana, University of Milano-Bicocca, Italy</li> <li>Valentina Lenarduzzi, University of Oulu, Finland</li> </ul> <h2>Content Overview</h2> <p>This replication package contains the following materials:</p> <ul> <li><strong>Tables:</strong> Excel files that include all hypothesis testing data, including normality tests for each hypothesis.</li> <li><strong>Data:</strong> RAW Qualitas Corpus dataset and aggregated SAT output.</li> <li><strong>SAT Instructions:</strong> A PDF file providing detailed instructions for the SAT setup and execution.</li> </ul> <h2>Contact Information</h2> <p>For any issues, questions, or further assistance, please do not hesitate to contact the authors of the paper. We are here to help!</p> </div> </div> </div> </div> </div>
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.