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390 results for “template”

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zenodo36/100

IS2 Template Brain

<p>An intersex, nc82-stained averaged brain constructed from&nbsp;18 male and&nbsp;16 female brains. Voxel size: (0.41, 0.41, 1.07) microns.&nbsp;<strong>If you make use of this data, please cite:</strong></p> <p>Sexual Dimorphism in the Fly Brain<br /> Sebastian Cachero, Aaron D. Ostrovsky, Jai Y. Yu, Barry J. Dickson, Gregory S.X.E. Jefferis<br /> http://dx.doi.org/10.1016/j.cub.2010.07.045</p>

opencc-zeroJun 2014View details →
zenodo36/100

Cell07 Template Brain

<p><strong>If you make use of this data, please cite:</strong></p> <p><strong>Comprehensive Maps of Drosophila Higher Olfactory Centers: Spatially Segregated Fruit and Pheromone Representation</strong><br /> Gregory S.X.E. Jefferis, Christopher J. Potter, Alexander M. Chan, Elizabeth C. Marin, Torsten Rohlfing, Calvin R. Maurer Jr., Liqun Luo<br /> http://dx.doi.org/10.1016/j.cell.2007.01.040</p> <p>&nbsp;</p> <p>This intersex, averaged template brain&nbsp;is an average of 16 co-registered, nc82-stained brains. The initial seed brain was female; 13 additional female and 2 male brains were registered to this seed and then all 16 were averaged. The reference includes the dorsal posterior quarter of the left brain hemisphere, a volume of approximately 168 &times; 168 &times; 87 microns cubed.</p>

opencc-zeroJun 2014View details →
zenodo36/100

T1 Template Brain

<p>&nbsp;<strong>If you make use of this data, please cite:</strong></p> <p><strong>Cellular Organization of the Neural Circuit that Drives Drosophila Courtship Behavior</strong><br /> Jai Y. Yu, Makoto I. Kanai, Ebru Demir, Gregory S. X. E. Jefferis, Barry J. Dickson<br /> http://dx.doi.org/10.1016/j.cub.2010.08.025</p> <p>A nrrd version of the original intersex&nbsp;template brain available from&nbsp;http://brainbase.imp.ac.at/bbweb, consisting of an average of&nbsp;45&nbsp;brains. Voxel size: (0.5488761,&nbsp;0.5488761, 1) microns.</p>

opencc-zeroJun 2014View details →
zenodo36/100

IBNWB Template Brain

<p>An extended, whole-brain version of the original&nbsp;IBN template brain made available from:</p> <p><strong>A Systematic Nomenclature for the Insect Brain</strong><br /> Kei Ito, Kazunori Shinomiya, Masayoshi Ito, J. Douglas Armstrong, George Boyan, Volker Hartenstein, Steffen Harzsch, Martin Heisenberg, Uwe Homberg, Arnim Jenett, Haig Keshishian, Linda L. Restifo, Wolfgang R&ouml;ssler, Julie H. Simpson, Nicholas J. Strausfeld, Roland Strauss, Leslie B. Vosshall, Insect Brain Name Working Group<br /> http://dx.doi.org/10.1016/j.neuron.2013.12.017</p> <p>The green channel (n-syb-GFP) of the tricolour confocal data provided was taken, duplicated and flipped about the medio-lateral axis using Fiji. The Fiji plugin &#39;Pairwise stitching&#39; was used to stitch the two stacks together with an offset of 392 pixels. This offset was chosen by eye as the one from the range of offsets 385&ndash;400 pixels that produced the most anatomically correct result. The overlapping region&#39;s intensity was set using the &#39;linear blend&#39; method.</p>

opencc-by-sa-4.0Jun 2014View details →
zenodo36/100

Drosophila virilis template brains

<p>Male and female symmetric averaged templates (10 and 11 brains, respectively) and intersex template brain for&nbsp;<em>Drosophila virilis</em>. Voxel size: (0.461, 0.461, 1) micron. Individual brains were imaged with a Zeiss 710 confocal microscope using an EC Plan-Neofluar 40 &times; / 1.30 NA oil objective and zoom factor 0.6, with the resulting images being stitched together using the &#39;Pairwise stitching&#39; plugin of Fiji.</p>

opencc-zeroJun 2014View details →
zenodo36/100

V2 ventral nerve cord template

<p>A nrrd version of the original intersex ventral nerve cord template available from http://brainbase.imp.ac.at/bbweb, consisting of an average of 44 VNCs. Voxel size: (0.6629126, 0.6629126, 1) microns.</p> <p><strong>If you make use of this data, please cite:</strong></p> <p><strong>Cellular Organization of the Neural Circuit that Drives Drosophila Courtship Behavior</strong><br /> Jai Y. Yu, Makoto I. Kanai, Ebru Demir, Gregory S. X. E. Jefferis, Barry J. Dickson<br /> http://dx.doi.org/10.1016/j.cub.2010.08.025</p>

opencc-by-sa-4.0Jan 2015View details →
zenodo36/100

VNCIS1 ventral nerve cord template

<p>An intersex, nc82-stained averaged ventral nerve cord constructed from 29 male and 21 female brains. Voxel size: (0.43, 0.43, 1.06) microns.&nbsp;<strong>If you make use of this data, please cite:</strong></p> <p>Sexual Dimorphism in the Fly Brain<br /> Sebastian Cachero, Aaron D. Ostrovsky, Jai Y. Yu, Barry J. Dickson, Gregory S.X.E. Jefferis<br /> http://dx.doi.org/10.1016/j.cub.2010.07.045</p>

opencc-by-sa-4.0Jan 2015View details →
zenodo36/100

Template for implementation of the Surface Rupture Database (SURE)

<p>The structure of the "surface rupture database" (SURE) has been discussed during a workshop in Paris. Please find details at www.earthquakegeology.com/materials/projects/1620R-report.pdf </p> <p> </p>

opencc-by-4.0Dec 2016View details →
zenodo36/100

Empirical Stellar Templates Associated with "An Empirical Template Library of Stellar Spectra for a Wide Range of Spectral Classes, Luminosity Classes, and Metallicities Using SDSS BOSS Spectra"

<p>This is the dataset of empirical stellar templates associated with the publication "An Empirical Template Library of Stellar Spectra for a Wide Range of Spectral Classes, Luminosity Classes, and Metallicities Using SDSS BOSS Spectra", which has been accepted for publication in the Astrophysical Journal Supplements. </p>

opencc-by-4.0Feb 2017View details →
zenodo36/100

Soil BON Earthworm - Community data template

<p>The Soil BON Earthworm consortium built a data template for everyone to use and format their data, so that it can be collated in a straightforward way. The template is an updated version of the one developed for the EUdaphobase COST Action <a href="https://www.zotero.org/google-docs/?ar5Q1g">(Tsiafouli et al. 2022)</a>. More information on Soil BON Earthworm initiative and the data templates created are available in the associated publication (insert DOI when available).</p><p>It is composed of different leaflets:</p><ol><li>"Readme": this leaflet contains all column names from the next leaflet and provides the necessary information to properly fill the information needed.</li><li>"Template to fill with data": this leaflet is composed of several columns where the data provider can enter the information on dataset, site, methodology and taxa sampled. This leaflet is to be filled with density data, and another file should be produced for biomass data.</li><li>"drop down list": this leaflet is non-modifiable and contains the different lists from which values are taken for certain variables, such as soil type which follow the WRB FAO classification <a href="https://www.zotero.org/google-docs/?XHAIOm">(IUSS Working Group WRB 2015)</a>.</li></ol>

opencc-by-4.0Dec 2023View details →
dryad36/100

Template-specific optimization of NGS genotyping pipelines reveals allele-specific variation in MHC gene expression

<p>Using high-throughput sequencing for precise genotyping of multi-locus gene families, such as the Major Histocompatibility Complex (MHC), remains challenging, due to the complexity of the data and difficulties in distinguishing genuine from erroneous variants. Several dedicated genotyping pipelines for data from high-throughput sequencing, such as next-generation sequencing (NGS), have been developed to tackle the ensuing risk of artificially inflated diversity. Here, we thoroughly assess three such multi-locus genotyping pipelines for NGS data, the DOC method, AmpliSAS and ACACIA, using MHC class IIβ datasets of three-spined stickleback gDNA, cDNA, and "artificial" plasmid samples with known allelic diversity. We show that genotyping of gDNA and plasmid samples at optimal pipeline parameters was highly accurate and reproducible across methods. However, for cDNA data, gDNA-optimal parameter configuration yielded decreased overall genotyping precision and consistency between pipelines. Further adjustments of key clustering parameters were required tο account for higher error rates and larger variation in sequencing depth per allele, highlighting the importance of template-specific pipeline optimization for reliable genotyping of multi-locus gene families. Through accurate paired gDNA-cDNA typing and MHC-II haplotype inference, we show that MHC-II allele-specific expression levels correlate negatively with allele number across haplotypes. Lastly, sibship-assisted cDNA-typing of MHC-I revealed novel variants linked in haplotype blocks and a higher-than-previously-reported individual MHC-I allelic diversity. In conclusion, we provide novel genotyping protocols for the three-spined stickleback MHC-I and -II genes and evaluate the performance of popular NGS-genotyping pipelines. We also show that fine-tuned genotyping of paired gDNA-cDNA samples facilitates amplification bias-corrected MHC allele expression analysis.</p>

opencc-zeroJan 2024View details →
zenodo36/100

Artifact for "Inside Bug Report Templates: An Empirical Study on Bug Report Templates in Open-Source Software"

<p>This is the artifact for the&nbsp;paper "Inside Bug Report Templates: An Empirical Study on Bug Report Templates in Open-Source Software".</p> <p><strong>What the artifact&nbsp;does:</strong><br>1) a questionnaire that we used for our online survey (PDF);<br>2) the valid responses of our online survey (CSV).</p> <p>3) the code of preprocessing (.py).</p> <p>4) the dataset of preprocessing and labeling (CSV).</p>

opencc-by-4.0Apr 2024View details →
zenodo36/100

Fit to template of horseback shapes

<p>The&nbsp; csv file contains the polynomial coefficients of&nbsp; &nbsp;10th order polynoms for&nbsp; reconstructing the different horses profiles on templates obtained by a professional horse saddler.</p> <p>All the dimensions in x and y are in cm.</p> <p>Column 1 contains an id for each horse.</p> <p>Columns&nbsp; 2 and 3 contain the bounds of the intervals on the x axis.</p> <p>Columns 4 to&nbsp; 14&nbsp;give&nbsp;the coefficients of the polynom for the CL curve</p> <p>Columns&nbsp; &nbsp;15 and 16&nbsp;contain the bounds of the intervals on the x axis.</p> <p>Columns 17 to&nbsp; 27 give&nbsp;the coefficients of the polynom for the CT1 curve</p> <p>Columns&nbsp; 28 and 29&nbsp;contain the bounds of the intervals on the x axis.</p> <p>Columns 30&nbsp;to&nbsp; 40 give&nbsp;the coefficients of the polynom for the CT2 curve</p> <p>Columns&nbsp; 41 and 42&nbsp;contain the bounds of the intervals on the x axis.</p> <p>Columns 43 to&nbsp; 53&nbsp;give&nbsp;the coefficients of the polynom for the CT3 curve</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

Template dataset for cell simulation

<p>Dataset with templates of actual cells observed through fluorescent microscopy. The zip archive contains:</p> <ul> <li>a library of 3D cell and nucleus shapes, in addition of 2D protrusion areas.</li> <li>precomputed distance maps.</li> <li>an index in a CSV file.</li> </ul> <p>&nbsp;</p> <p>Original dataset comes from&nbsp;https://doi.org/10.5281/zenodo.1413489</p> <p>Template dataset initially used by&nbsp;https://github.com/fish-quant/sim-fish/tree/main</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

Analysis Templates for Pohl, Macias, Coleman, and Gordon (2022)

<p>Archive of the templates used for the analysis of Fermi-LAT data that is presented in Pohl et al. (2022). Consult the Readme file before use.</p>

opencc-by-4.0Feb 2022View details →
zenodo36/100

Research data supporting "Tunable microgel-templated porogel (MTP) bioink for 3D bioprinting applications"

<p>Raw research data supporting Ouyang L. et al., 2022, Advanced Healthcare Materials</p> <p><a href="https://doi.org/10.1002/adhm.202200027">https://doi.org/10.1002/adhm.202200027</a></p>

opencc-by-4.0Jan 2022View details →
zenodo36/100

Telemeeting Profile Template

<p>This data set contains a Telemeeting Profile Template, a tool that has been developed for a holistic characterization of telemeetings from a Quality of Experience (QoE) perspective. For more information, see our survey paper on telemeeting QoE, which will be published shortly:</p> <p>Janto Skowronek et al,<br> Quality of Experience in Telemeetings and Videoconferencing: A Comprehensive Survey<br> accepted for publication on May 5, 2022<br> IEEE Access<br> 2022</p>

opencc-by-4.0May 2022View details →
dryad36/100

Selectivity improvement of polysulfone-zeolite templated carbon membrane by annealing and coating treatment for CO2/CH4 and H2/CH4 separation

<p>Natural gas, which majorly consists of methane (CH4), is a renewable energy source widely used as fuel, as well as hydrogen (H2). However, in its production process of each gas containing other impurity gasses. Therefore, membrane technology is needed to separate the gasses from the impurities. Mixed Matrix Membrane (MMM) is a more promising membrane compared to the others. Zeolite Templated Carbon-based MMM offers a good separation performance because of ZTC's large surface area and well-defined pore structure. However, the interfacial void in MMM is challenging to be prevented, which contributes to the reduced separation performance. This study aims to enhance separation performance by modifying membrane surfaces using various methods. MMM PSF/ZTC modified by annealing at 120, 150, and 190 °C; coating using 0.01, 0.03, and 0.05 mol tetramethylorthosilicate (TMOS); and both combinations annealing at 190 °C and coating using 0.03 mol TMOS. MMM PSF/ZTC was successfully significantly improved CO2/CH4 selectivity by both combinations of annealed at 190 °C and coated 0.03 mol TMOS from 1.37 to 5.90 (331%) and H2/CH4 selectivity by coating with 0.03 mol TMOS from 4.58 to 65.76 (1378%). The enhancement of selectivity was due to structural changes of the membrane that was denser and smoother, which SEM and AFM observed. In this study, annealing and coating treatment are the methods that can use for improving the polymer matrix and filler particle adhesion.</p>

opencc-zeroMay 2022View details →
zenodo36/100

Data for "Impact of Surface Adsorbates and Dimensionality on Templating of Halide Perovskites"

<p>This record contains databases with data from density functional theory calculations used for training of a neuroevolution potential (NEP) for 2D halide perovskites.&nbsp;</p>

opencc-by-4.0May 2024View details →
zenodo36/100

[Data augmentation in a TTL] - Fictive dataset (27.5M) with up to 5k reactions per template // (13'953 template extracted from USPTO-FULL IBM version)

<p>Full generated fictive dataset, containing 27.5M reactions with up to 5000 reactions per radius 1 reaction template (13'953 reaction templates from USPTO-full, IBM version).</p> <p>Title of the manuscript:</p> <p>"Data augmentation in a Triple Transformer Loop retrosynthesis model"</p> <p>Abstract:&nbsp;</p> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div dir="auto"> <div>Reactions in the US Patent Office (USPTO) are biased towards a few over-represented reaction types, which potentially limits its usefulness for computer-assisted synthesis planning (CASP). To obtain an equilibrated dataset, we applied retrosynthesis templates to USPTO molecules as products (P) to generate starting materials (SM). We then used transformer T2 from our recently reported triple transformer loop (TTL) retrosynthesis model to predict reagents (R) for the SM&reg;P reaction. Finally, we validated the prediction by requesting a high confidence prediction (&gt;95%) for the prediction of P from SM+R by TTL transformer T3. We generated up to 5,000 reactions per template, resulting in 27.5 million validated fictive reactions covering the chemical space of the original UPSTO dataset. To exemplify the use of this dataset, we show that a single-step retrosynthesis transformer model trained with a template equilibrated subset of 1,097,374 fictive reactions outperforms the corresponding model trained on USPTO reactions only.</div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div></div>

opencc-by-4.0Jul 2024View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record