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1,291 results for “gap”

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zenodo40/100

Figure 5 in Linking a gap, First record of dusky-gilled mudskipper Periophthalmus variabilis Eggert, 1935 (Perciformes: Gobiidae) in southern Sumatra, Indonesia

Figure 5. Raised first and second dorsal fins of P. variabilis with characteristic pigmentation (© M. Iqbal).

opencc-by-4.0Nov 2019View details →
zenodo40/100

Figure 4 in Linking a gap, First record of dusky-gilled mudskipper Periophthalmus variabilis Eggert, 1935 (Perciformes: Gobiidae) in southern Sumatra, Indonesia

Figure 4. Ventral view of P. variabilis showing pelvic fins with frenum and the inner rays fused at their base (© M. Iqbal).

opencc-by-4.0Nov 2019View details →
zenodo40/100

Figure 1 in Linking a gap, First record of dusky-gilled mudskipper Periophthalmus variabilis Eggert, 1935 (Perciformes: Gobiidae) in southern Sumatra, Indonesia

Figure 1. Distribution of Periophthalmus variabilis, circles indicate previous records, triangle represents most recent record in southern Sumatra, Sugihan estuary, 02°55'41.8''S; 104°45'51.6''E.

opencc-by-4.0Nov 2019View details →
zenodo40/100

Figure 2 in Linking a gap, First record of dusky-gilled mudskipper Periophthalmus variabilis Eggert, 1935 (Perciformes: Gobiidae) in southern Sumatra, Indonesia

Figure 2. Location at Sugihan estuary in southern Sumatra where P. variabilis was found (© M. Iqbal).

opencc-by-4.0Nov 2019View details →
zenodo40/100

Analysis of gaps in rapeseed (Brassica napus L.) collections in European genebanks - supplementary data

<p>Species distribution modelling (or ecological niche modelling) was used to predict the effects of climate change on the future distribution of the wild relatives of Brassica napus L. in Europe and countries bordering the Mediterranean Sea. Modelling procedures followed the methods described by Aguirre-Gutierrez et al. 2017 (10.1111/ddi.12573) and van Treuren et al. 2017+2020 (10.1016/j.biocon.2017.10.003; 10.1016/j.gecco.2020.e01054).</p>

opencc-by-4.0Jun 2023View details →
zenodo40/100

Ivy Gap GBM Gene Expression

<p><strong>Abstract:</strong></p> <p>The Ivy Glioblastoma Atlas Project represents a fundamental tool for investigating the cellular and molecular underpinnings of glioblastoma. It offers an accessible online atlas and database containing valuable clinical and genomic information, which will undoubtedly facilitate future studies on glioblastoma pathogenesis, diagnosis, and therapeutic approaches. Glioblastoma is a highly aggressive brain tumor with a bleak prognosis, and its intricate molecular and cellular characteristics have not been fully elucidated in relation to conventional diagnostic histologic features. The dataset provided is comprised of gene expression values for each sample and gene.&nbsp;</p> <p><strong>Inspiration:</strong></p> <p>This dataset was uploaded to UBRITE for GTKB project.&nbsp;</p> <p><strong>Acknowledgments:</strong></p> <p>Puchalski RB, Shah N, Miller J, et al. An anatomic transcriptional atlas of human glioblastoma. Science. 2018;360(6389):660-663. doi:10.1126/science.aaf2666</p> <p><strong>U-BRITE last update:&nbsp;</strong>07/28/2023</p> <p>&nbsp;</p>

opencc-by-4.0Jul 2023View details →
zenodo40/100

Molecular dynamics simulation data 3: Structure of the connexin-43 gap junction channel in a putative closed state

<p>Molecular dynamics data for the manuscript Qi C.*, Acosta-Gutierrez S.*, Lavriha P., Othman A., Lopez-Pigozzi D., Bayraktar E., Schuster D., Picotti P., Zamboni N., Bortolozzi M., Gervasio F.L., Korkhov V.M.&nbsp;Structure of the connexin-43 gap junction channel in a putative closed state. eLife (2023)&nbsp;<a href="https://doi.org/10.7554/eLife.87616.2">https://doi.org/10.7554/eLife.87616.2</a></p> <p>The dataset includes:&nbsp;Production run&nbsp;gromacs trajectories for the Cx43 gap junction channel (500 mV)</p>

opencc-by-4.0Jul 2023View details →
zenodo40/100

Molecular dynamics simulation data 2: Structure of the connexin-43 gap junction channel in a putative closed state

<p>Molecular dynamics data for the manuscript Qi C.*, Acosta-Gutierrez S.*, Lavriha P., Othman A., Lopez-Pigozzi D., Bayraktar E., Schuster D., Picotti P., Zamboni N., Bortolozzi M., Gervasio F.L., Korkhov V.M.&nbsp;Structure of the connexin-43 gap junction channel in a putative closed state. eLife (2023)&nbsp;<a href="https://doi.org/10.7554/eLife.87616.2">https://doi.org/10.7554/eLife.87616.2</a></p> <p>The dataset includes:</p> <p>1. The&nbsp;starting coordinates, topology, MD inputs</p> <p>2.&nbsp;Production run&nbsp;gromacs trajectories for the Cx43 hemichannel</p>

opencc-by-4.0Jul 2023View details →
zenodo40/100

The Air Listening Station: Bridging the gap between Sound Art and Sonification - Sonification examples

<p><strong>Example audio files:</strong></p> <p>1)&nbsp;aesthetic_direction_01.mp3 --&gt; Initial aesthetic direction/proof of concept created using 1 hour of PM_10 and PM_2.5 data rendered at a 10:1 ratio (i.e. 60 minutes of air quality data results in 6 minutes of audio). &nbsp;Created using&nbsp;the Ultimate Grainer module of Ajax Sound Studio&rsquo;s Cecilia 5 audio signal processing environment.</p> <p>2)&nbsp;sample sonification - original - good AQ - 5x bad AQ.mp3 --&gt; contains several example outputs created using the sonification instrument created in Supercollider presented during&nbsp;the <a href="https://radioart.zone/sunday-28-august">radio art zone broadcast on August 28, 2022</a></p> <ul> <li>[0:00] - original field recording before processing</li> <li>[0:30] - example of &quot;good&quot; air quality data</li> <li>[1:02] - example of &quot;bad&quot; air quality data #1</li> <li>[2:10] - example of &quot;bad&quot; air quality data #2</li> <li>[2:45] - example of &quot;bad&quot; air quality data #3</li> <li>[3:08] - example of &quot;bad&quot; air quality data #4</li> <li>[3:38] - example of &quot;bad&quot; air quality data #5</li> </ul>

opencc-by-4.0Aug 2023View details →
zenodo40/100

Dataset: Impact of lateral gap on flow distribution, backwater rise, and turbulence generated by a logjam

<p>This dataset includes flow measurements and wood accumulation characteristics of flume experiments conducted at the Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich.</p>

opencc-by-4.0Oct 2023View details →
zenodo40/100

Mapping Nature's Contributions to People provided by Low Trophic Species aquaculture and knowledge gaps

<p>This dataset was generated by the work on quantification of Nature&rsquo;s Contributions to People (NCPs) provided by Low Trophic Species (LTS) aquaculture. As a first step of this work, the identification of the NCPs provided by LTS aquaculture (based on the case studies investigated within AquaVitae) and the identification of current knowledge gaps in terms of qualitative contributions of LTS aquaculture to the NCPs was performed based on expert judgements and literature review.</p> <p>The ecosystem services framework from IPBES &ndash; Nature&rsquo;s Contributions to People was adopted in this work.</p>

opencc-by-4.0Dec 2022View details →
zenodo40/100

MODIS Daily Cloud-gap-filled Fractional Snow Cover Dataset of the Asian Water Tower Region (2000-2022)

<p>The Asia Water Tower region, with the Qinghai-Tibet Plateau at its core, is the most widespread region of snow cover on Earth, except for the North and South Poles. The topographic heterogeneity of the Asian Water Tower region is so great that the snow cover is thin and patchy, resulting in a highly time-varying snow cover in the region, and therefore daily-scale fractional snow cover data are urgently needed. This dataset is based on the MODIS&nbsp;surface reflectance product MO/YD09GA product, and the MODIS daily cloud-free fractional snow cover dataset for the Asian Water Tower region from 2000 to 2022 was produced using the MESMA-AGE algorithm and the MSTI algorithm. The high spatial resolution Landsat-8 image was taken as the "ground truth", the RMSE was 0.16, and the MAE was 0.10. This dataset has a time series from 26 February 2000 to 31 December 2022 with a spatial resolution of 0.005°, which can provide quantitative snow cover information on the spatial distribution of snow for mountain hydrological models, land surface models, numerical weather forecasts, etc.</p>

opencc-by-4.0Oct 2023View details →
dryad40/100

Multiple disturbances, multiple legacies: Fire, canopy gaps and deer jointly change the forest seed bank

Open the record for dataset details and reuse information.

publicNov 2024View details →
dryad40/100

Bridging biosafety and biosecurity gaps: DURC and ePPP policy insights from U.S. institutions

Open the record for dataset details and reuse information.

publicSep 2024View details →
dryad40/100

Sexually dimorphic eye-size in Dragonfishes, a response to a bioluminescent signaling gap

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publicJul 2024View details →
dryad40/100

Data for linked disturbance in the temperate forest: earthworms, deer, and canopy gaps

Open the record for dataset details and reuse information.

publicMar 2023View details →
dryad40/100

Date From: The myriad of complex demographic responses of terrestrial mammals to climate change and gaps of knowledge: A global analysis

Open the record for dataset details and reuse information.

publicMar 2021View details →
dryad40/100

Data from: Assessing the recovery gap in forest restoration within the Brazilian Atlantic Forest

Open the record for dataset details and reuse information.

publicMar 2025View details →
dryad40/100

Canopy gaps facilitate upslope shifts in montane conifers but not in temperate deciduous trees in the Northeastern United States

Open the record for dataset details and reuse information.

publicAug 2022View details →
dryad40/100

Gaps in DNA sequence libraries for Macaronesian marine macroinvertebrates imply decades till completion and robust monitoring

Open the record for dataset details and reuse information.

publicMay 2021View details →

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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

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