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4,694 results for “data analysis”
A Tool for Uncertainty Quantification in Reconstructing Sparse Water Quality Time Series Data to Assess Risk Metrics for Watershed Health and TMDL Analysis
<p>The uploaded file contains the input and output data which can be used to reproduce the results in the research article 'Uncertainty Quantification in Reconstruction of Sparse Water Quality Time Series: Implications for Watershed Health and Risk-Based TMDL Assessment'. Please refer to the file '<a href="https://zenodo.org/api/files/31b59cce-8eb2-4ee7-93aa-61474c6f6359/dst_2019_SJRW_TP_TDS.zip?versionId=2af2b54d-d5fb-4720-919d-de2e827595e2">dst_2019_SJRW_TP_TDS.zip'</a> for updated files..</p>
Data from "Corset: enabling differential gene expression analysis for de novo assembled transcriptomes"
<p>This dataset contains de novo transcriptome assemblies for three publicly available RNA-seq dataset (SRA055442, SRR453566-SRR453571 and GSE37704 ). For each assembly we also provide a table with the read counts per contig, the output from corset (clusters and counts), and the results from a genome-based analysis. This dataset was used to assess the performance of the corset software. More detail is provided in the paper: Nadia M Davidson and Alicia Oshlack,<strong> </strong>Corset: enabling differential gene expression analysis for de novo assembled transcriptomes, <em>Genome Biology</em> 2014, <strong>15</strong>:410. http://genomebiology.com/2014/15/7/410/abstract</p>
Model, data, and analysis for Negative Niche Construction Favors the Evolution of Cooperation
<p>This repository contains the model, data, and analysis corresponding to <em>Negative Niche Construction Favors the Evolution of Cooperation</em> as submitted for review by Brian D. Connelly, Katherine J. Dickinson, Sarah P. Hammarlund, and Benjamin Kerr. Contents are released to the public domain under the Creative Commons CC0 License.</p>
Data sets for orthologous target pair analysis
<p>The set of all 803 originally identified orthologous target pairs (OTPs) and the subset of 222 OTPs with at least 10 shared compounds are provided herein. For each OTP both organisms, the target, the number of shared compounds,the OTP category, and the number of reference articles is reported. In addtion, the list of all 1149 candidate compounds and their human target assignments is provided. </p>
Model, Data, and Analysis Scripts for The Evolution of Cooperation by the Hankshaw Effect
<p>Model, Data, and Analysis Scripts for The Evolution of Cooperation by the Hankshaw Effect as submitted</p>
Data sets for SAR progression analysis
<p>Four compound data sets assembled from ChEMBL are provided that have been subjected to SAR progression analysis, to be published in Journal of Medicinal Chemistry. </p>
Trophic-meta-analysis: Second release of tritrophic meta-analysis data, code and appendices
<p>Data, R script and appendices for "Interaction strength and the impact of introduced omnivores: A meta-analysis of introduced aquatic invasive species" submitted to Oikos</p>
Raw data and analysis pipeline for producing figures in F.W. Carter, et. al., 2016
<p>This data release accompanies a manuscript submitted to IEEE Transactions on Applied Superconductivity on Sept. 6, 2016. If accepted, DOI of the publication will be linked to this.</p> <p>This data release (and accompanying JuPyter notebook) were used to generate all of the figures in the manuscript. The software package used to crunch the data is archived here: http://dx.doi.org/10.5281/zenodo.61512</p>
FIGURES 34 37. Lamyctes hellyeri n in A new blind Lamyctes (Chilopoda: Lithobiomorpha) from Tasmania with an analysis of molecular sequence data for the Lamyctes Henicops Group
FIGURES 34 37. Lamyctes hellyeri n. sp. QVMAG 23: 23048, female, pretarsus of leg 14, scales 10 m. 34 36, anterior, posterior, and ventral views; 37, detail of lateral pore and ornament on scutes of main claw.
FIGURES 11 17. Lamyctes hellyeri n in A new blind Lamyctes (Chilopoda: Lithobiomorpha) from Tasmania with an analysis of molecular sequence data for the Lamyctes Henicops Group
FIGURES 11 17. Lamyctes hellyeri n. sp. 11, 14 17, QVMAG 23: 23046, female. 11, anterior part of head shield and basal part of antennae, scale 100 m; 14, sensilla on dorsal side of antenna, scale 10 m; 15 16, antennal articles, dorsal side, scales 50 m; 17, cephalic pleurite with Tömösváry organ, scale 50 m. 12 13, QVMAG 23: 23047, female. 12, ventral view of clypeus and labrum, scale 100 m; 13, labral midpiece and inner parts of sidepieces, scale 30 m.
FIGURES 1 4 in A new blind Lamyctes (Chilopoda: Lithobiomorpha) from Tasmania with an analysis of molecular sequence data for the Lamyctes Henicops Group
FIGURES 1 4. Lamyctes coeculus (Brölemann). 1, 3, AM KS 57961, female, Mellong Range, NSW, Australia. 2, 4, MCZ DNA 100472, female, Cerro San Javier, Tucumán, Argentina. 1 2, ventral view of head, scales 100 m; 3 4, dental margin of maxillipede coxosternite, scales 50 m.
FIGURES 18 25. Lamyctes hellyeri n in A new blind Lamyctes (Chilopoda: Lithobiomorpha) from Tasmania with an analysis of molecular sequence data for the Lamyctes Henicops Group
FIGURES 18 25. Lamyctes hellyeri n. sp. QVMAG 23: 23046, female. 18, ventral view of maxillipede, scale 100 m; 19 20, dental margin of maxillipede coxosternite, scales 50 m, 10 m; 21, tarsus and claw of second maxilla, scale 50 m; 22, distal part of tarsus and claw of second maxilla, scale 10 m; 23, coxal projections and telopods of first maxillae, scale 50 m; 24, first maxillae, scale 100 m; 25, plumose setae on inner margins of telopods of first maxillae, scale 10 m.
Data to initialize a TAD_Pathways Analysis
<p>Dataset is required for a TAD_Pathways analysis (see https://github.com/greenelab/tad_pathways_pipeline).</p> <p>Archived folder includes a TAD based gene index file, curated SNPs from the NHGRI-EBI GWAS catalog, and TAD based genes and SNPs for each GWAS.</p>
Data and analysis scripts for Zizka et al., Finding needles in the haystack: Where to look for rare species in the American tropics
<p>The analysis scripts and data from: Zizka A, ter Steege H, Pessoa MDC, Antonelli A (2017) Finding needles in the haystack: Where to look for rare species in the American tropics. Ecography.</p>
Synthetic Smart Card Data for the Analysis of Temporal and Spatial Patterns
<p>This is a synthetic smart card data set that can be used to test pattern detection methods for the extraction of temporal and spatial data. The data set is tab seperated and based on a stylized travel pattern description for city of Utrecht in The Netherlands and is developed and used in Chapter 6 of the PhD Thesis of Paul Bouman. </p> <p>This dataset contains the following files:</p> <ul> <li>journeys.tsv : the actual data set of synthetic smart card data</li> <li>utrecht.xml : the activity pattern definition that was used to randomly generate the synthethic smart card data</li> <li>validate.ref : a file derived from the activity pattern definition that can be used for validation purposes. It specifies which activity types occur at each location in the smart card data set.</li> </ul>
Simulated data used in "The importance of censoring in competing risks analysis of the subdistribution hazard"
<p>The simulated data used for analysis in "The importance of censoring in competing risks analysis of the subdistribution hazard". Simulated using the method described in Additional file 1.<br> <br> <strong>Warning: Large file.</strong> Contains 1000 datasets of 300 observations each, for each of 105 parameter combinations (31,500,000 rows). Some programs (e.g. Excel) will not be able to open it in full.</p> <p>csv file with columns:</p> <p><strong>p.comp:</strong> risk of the competing event in exposure group A for this scenario [0 to 0.30 in increments of 0.05]<br> <strong>lnb.cens:</strong> log(hazard ratio) for loss to follow-up in old versus young individuals for this scenario [0 to 1 in increments of 0.25]<br> <strong>lnb.evt:</strong> log(subdistribution hazard ratio) for the event of interest in exposure group B vs group A for this scenario [0, 0.5, 1]<br> <strong>sim:</strong> ID of the simulated dataset for this scenario [1-1000]<br> <strong>exposure:</strong> exposure group (0 = A, 1 = B) of this individual<br> <strong>age:</strong> age group (0 = young, 1 = old) of this individual<br> <strong>time:</strong> time-to-event or censoring for this individual<br> <strong>evtcode:</strong> event type (0 = censoring, 1 = event of interest, 2 = competing event)<br> <strong>censcode:</strong> type of censoring (1 = end-of-study, 2 = loss to follow-up)</p>
EBSD data for HRDIC analysis in AZ31
<p>EBSD data set obtained from the HRDCI analysis in an AZ31 mg alloy surface after deformation without removing the gold speckles. The map was obtained using a CamScan MX2000 equipped with an Oxford Instruments EBSD detector at 25 kV and using step size of 0.23 µm.</p> <p>This EBSD data set was obtained in the same region where the HRDIC analysis was performed for our publication entitled " Why magnesium is not brittle: a quantitative study on the accommodation of deformation incompatibility". The HRDIC data set can be found in https://doi.org/10.5281/zenodo.345313 while the notebook to visualise data is allocated in https://doi.org/10.5281/zenodo.376503.</p> <p>Accompanying the EBSD data set, images of the IPF representation in the three sample axis and the Schmid factor for basal slip when loading respect to the X axis (horizontal respect to the images)</p> <ul> <li>EBSD for HRDIC in AZ31 IPF-legend.tif --> Legend for the different IPF maps</li> <li>EBSD for HRDIC in AZ31 IPF-X.tif --> EBSD map represented respect to the X-axis (horizontal)</li> <li>EBSD for HRDIC in AZ31 IPF-X.tif --> EBSD map represented respect to the Y-axis (vertical)</li> <li>EBSD for HRDIC in AZ31 IPF-X.tif --> EBSD map represented respect to the Z-axis (observation axis)</li> <li>EBSD for HRDIC in AZ31 m-Basal-legend.tif --> Legend for the Schmid factor for Basal slip map</li> <li>EBSD for HRDIC in AZ31 m-Basal.tif --> Schmid factor values for Basal slip</li> <li>EBSD for HRDIC in AZ31.cpr --> Raw data, .cpr format</li> <li>EBSD for HRDIC in AZ31.crc --> Raw data, .crc format</li> <li>EBSD for HRDIC in AZ31.txt --> Raw data, .txt format</li> </ul> <p> </p>
Data for analysis in "Towards optimal cosmological parameter recovery from compressed bispectrum statistics"
<p>Measures of the three point function extracted from a suite of simulations using 4 different estimators: namely, the bispectrum, modal estimator, integrated bispectrum, line correlation function. Also supplied are power spectrum measures across the same simulations. <br> <br> The measures are done across 200 fiducial and 60 non-fiducial cosmology simulations, at 3 redshifts. Further details on what was done can be attained by reading the document, Overview.md/Overview.pdf, attached to the bundle. Even more details can be acquired by reading the paper this data was prepared for at https://arxiv.org/abs/1705.04392! </p>
Integrated field-aligned radar data and analysis results
<p>Dataset used in "A statistical survey of heat input parameters into the cusp thermosphere" J. Geophys. Res. 2017, doi:10.1002/2016JA023594.</p>
Training material for small RNA-seq data analysis (Galaxy Training Network tutorial)
<p>The data provided here are part of a Galaxy Training Network tutorial that analyzes small RNA-seq (sRNA-seq) data from a study published by Harrington et al. (DOI:10.1186/s12864-017-3692-8) to detect differential abundance of various classes of endogenous short interfering RNAs (esiRNAs). The goal of this study was to investigate "connections between differential retroTn and hp-derived esiRNA processing and cellular location, and to investigate the potential link between mRNA 3’ end cleavage and esiRNA biogenesis." To this end, sRNA-seq libraries were constructed from triplicate <em>Drosophila</em> tissue culture samples under conditions of either control RNAi or RNAi knockdown of a factor involved in mRNA 3’ end processing, <em>Symplekin</em>. This dataset (GEO Accession: GSE82128) consists of single-end, size-selected, non-rRNA-depleted sRNA-seq libraries. Because of the long processing time for the large original files, we have downsampled the original raw data files to include only reads that align to a subset of interesting transcript features including: (1) transposable elements, (2) <em>Drosophila</em> piRNA clusters, (3) <em>Symplekin</em>, and (4) genes encoding mass spectrometry-defined protein binding partners of <em>Symplekin</em> from Additional File 2 in the indicated paper by Harrington et al. More details on features 1 and 2 can be found here: https://github.com/bowhan/piPipes/blob/master/common/dm3/genomic_features (piRNA_Cluster, Trn). All features are from the <em>Drosophila</em> genome Apr. 2006 (BDGP R5/<em>dm3</em>) release.</p>
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.