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1,037 results for “large-scale”
AndroZooOpen: Collecting Large-scale Open Source Android Apps for the Research Community
<p>The raw collected data for the paper</p>
Fig. 1 in Large-scale migration of a school shark, Galeorhinus galeus, in the Southwestern Atlantic
Fig. 1. Schematic representation of the depth-averaged ocean circulation in the Southwestern Atlantic Ocean (adapted from Matano et al., 2010) showing the geographical locations of tagging of Galeorhinus galeus [Triangle, Nuevo Gulf (NG), 42°30'S, 65°55'W, depth 100 m], newest recapture in Uruguayan shelf waters (Star, 35°30'S, 51°48'W – depth 290 m) and the two old recapture sites (Circle, Mar del Plata, 38°24'S, 57°18'W, depth 40 m and Canal Culebra, 40°24'S, 62°06'W - depth 15 m, Irigoyen et al., 2015). Additional geographical locations are indicated with acronyms: SMG = San Matías Gulf, VP = Valdés Peninsula, AB = Anegada Bay, PM = Punta Médanos, STSF = Subtropical Shelf Front. The thick curved lines represent the path of the major ocean currents. The black line is the 200m isobath. Colours indicate bottom temperature (a, c) and bottom salinity (b, d) and black arrows indicate the bottom shelf circulation extracted from a numerical model (Palma et al., 2008). The yellow and gray lines in the left panels indicate the 11 and 17 °C isotherms respectively. The red and cyan lines in the right panels indicate the 33.93 and 33.5 isohalines.
Fig. 2. A in Large-scale migration of a school shark, Galeorhinus galeus, in the Southwestern Atlantic
Fig. 2. A) Releasing of a tagged Galeorhinus galeus, B) the recaptured tag on August 17, 2015, and C) length size distribution of school sharks captured and tagged in Nuevo Gulf (~ 42°30'S, Argentina) during February 15, 2015.
Fig. 5 Lateral habitus a in Rapid, large-scale species discovery in hyperdiverse taxa using 1D MinION sequencing
Fig. 5 Lateral habitus a and diagnostic features of Megaselia
Data from "Large-scale CO spirals and complex kinematics associated with the T Tauri star RU Lup"
<p>Image cubes, self-calibrated visibilities, and self-calibration and imaging scripts for data from Huang et al., 2020, "Large-scale CO spirals and complex kinematics associated with the T Tauri star RU Lup," ApJ, 898, 140 (arXiv:2007.02974) </p> <p>The raw ALMA data can be found at the ALMA archive under program ID 2018.1.01201.S (PI: Jane Huang).</p> <p><strong>Scripts:</strong></p> <p>selfcal_C43-5.py, selfcal_C43-2.py, selfcal_ACA.py: self-calibration scripts for observation of RU Lup in various ALMA configurations</p> <p>imaging.py: imaging script used for all lines</p> <p>reductionutils.py can be downloaded from <a href="https://zenodo.org/record/3628656">https://zenodo.org/record/3628656</a></p> <p><strong>Measurement sets:</strong></p> <p>RULupcontinuum.ms.tgz: Continuum visibilities for "RULupallcontinuum.image.pbcor.fits" (the high-resolution ALMA continuum data can be found on the <a href="https://bulk.cv.nrao.edu/almadata/lp/DSHARP/">DSHARP</a> page)</p> <p>RULup_12CO.ms.contsub.tgz: Continuum-subtracted visibilities for the <sup>12</sup>CO J=2-1 line toward RU Lup</p> <p>RULup_12CO_nocontsub.ms.tgz: Visibilities for the <sup>12</sup>CO J=2-1 line (no continuum subtraction) toward RU Lup, used to make the 'RULup_12COpeakintensity.fits' file.</p> <p>RULup_13CO.ms.contsub.tgz: Continuum-subtracted visibilities for the <sup>13</sup>CO J=2-1 line toward RU Lup</p> <p>RULup_C18O.ms.contsub.tgz: Continuum-subtracted visibilities for the C<sup>18</sup>O J=2-1 line toward RU Lup</p> <p>RULup_DCOp.ms.contsub.tgz: Continuum-subtracted visibilities for the DCO<sup>+</sup> J=3-2 line toward RU Lup</p> <p><strong>Images: </strong></p> <p>RULup12CO.1sigcut.pbcor.mom0.fits: Integrated intensity map of <sup>12</sup>CO J=2-1 appearing in Fig. 1</p> <p>RULup12CO.pbcor.mom1.fits: <sup>12</sup>CO J=2-1 intensity-weighted velocity map appearing in Fig. 1</p> <p>RULup13CO.pbcor.mom0.fits: Integrated intensity map of <sup>13</sup>CO J=2-1 appearing in Fig. 1</p> <p>RULup13CO.pbcor.mom1.fits: <sup>13</sup>CO J=2-1 intensity-weighted velocity map appearing in Fig. 1</p> <p>RULupC18O.pbcor.mom0.fits: Integrated intensity map of C<sup>18</sup>O J=2-1 appearing in Fig. 1</p> <p>RULupC18O.pbcor.mom1.fits: C<sup>18</sup>O J=2-1 intensity-weighted velocity map appearing in Fig. 1</p> <p>RULup12CO.image.pbcor.fits: <sup>12</sup>CO J=2-1 image cube appearing in Fig. 2</p> <p>RULupC18O.image.pbcor.fits: C<sup>18</sup>O J=2-1 image cube appearing in Fig. 2</p> <p>RULup13CO.image.pbcor.fits: <sup>12</sup>CO J=2-1 image cube appearing in Fig. 3</p> <p>RULup_12COpeakintensity.fits: Peak intensity image of <sup>12</sup>CO used to make Figure 4</p> <p>RULupDCOp.pbcor.mom0.fits: Integrated intensity map of DCO<sup>+</sup> J=3-2 appearing in Fig. 10</p> <p>RULupDCOp.image.pbcor.fits: DCO<sup>+</sup> J=3-2 image cube appearing in Fig. 11</p> <p>RULupallcontinuum.image.pbcor.fits: Continuum image appearing in Fig. 12</p> <p>RULup12COinitial.mask.image.fits: <sup>12</sup>CO CLEAN mask shown in Fig. 13</p> <p> </p>
A large-scale wide-baseline light field dataset - Part II
<p>This dataset is the Part II of a large-scale, synthetic wide-baseline light field dataset (called WLF), including 16 light fields. </p> <p>Each light field provides 9x9 angular (RGB) images and ground truth disparities. This light field dataset involves the spatial resolution (1920x1080) images only.</p> <p>The dataset is originally created for training the deep learning-based models for depth estimation. You might use this dataset for other tasks if possible. </p> <p>You might also have a try to play with this dataset using our code in https://github.com/YanWQ/LLF-Net.</p>
ToxicoDB: an integrated database to mine and visualize large-scale toxicogenomic datasets (TGGATEs rat dataset)
<p>This data was generated by Igarashi Y, Nakatsu N, Yamashita T, Ono A, Ohno Y, Urushidani T, Yamada H. Open TG-GATEs: a large-scale toxicogenomics database. Nucleic Acids Res [Internet]. 2015 Jan;43(Database issue):D921–7. Available from: http://dx.doi.org/10.1093/nar/gku955 PMCID: PMC4384023. The data have been curated and analyzed using our open-source R package, <em>ToxicoGx</em> (<a href="http://bioconductor.org/packages/devel/bioc/html/ToxicoGx.html">http://bioconductor.org/packages/devel/bioc/html/ToxicoGx.html</a>) and are available publicly in the <em>ToxicoDB </em>web application (<a href="http://www.toxicodb.ca">www.toxicodb.ca</a>).</p>
ToxicoDB: an integrated database to mine and visualize large-scale toxicogenomic datasets (drug matrix dataset)
<p>This data was generated by Ganter B, Snyder RD, Halbert DN, Lee MD. Toxicogenomics in drug discovery and development: mechanistic analysis of compound/class-dependent effects using the DrugMatrix database. Pharmacogenomics [Internet]. 2006 Oct;7(7):1025–1044. Available from: http://dx.doi.org/10.2217/14622416.7.7.1025 PMID: 17054413. The data have been curated and analyzed using our open-source R package, <em>ToxicoGx</em> (<a href="https://cran.r-project.org/web/packages/ToxicoGx/">cran.r-project.org/web/packages/ToxicoGx</a>) and are available publicly in the <em>ToxicoDB </em>web application (<a href="http://www.toxicodb.ca">www.toxicodb.ca</a>).</p> <p> </p> <p> </p>
Large-scale RNAi screening uncovers new therapeutic targets in the human parasite Schistosoma mansoni
<p><span><span><span><span><span><span><span><span><span><span><span>Schistosomes kill 250,000 people every year. Treatment of schistosomiasis relies on a single drug (praziquantel). Unfortunately, a scarcity of molecular tools has hindered the discovery of new drug targets. Here, we describe a large-scale RNA interference screen in adult Schistosoma mansoni examining the function of 2,216 genes. We discovered 250 genes with phenotypes affecting neuromuscular function, tissue integrity, stem cell maintenance, and parasite survival. Leveraging these data, we prioritize compounds with activity against the parasites and uncover a pair of protein kinases (TAO and STK25) that cooperate to maintain muscle-specific mRNA transcription. Loss of either of these kinases results in paralysis and worm death in a mammalian host. These studies will expedite therapeutic development and invigorate studies of these neglected parasites. Large-scale RNAi screening uncovers new therapeutic targets in the human parasite Schistosoma mansoni.</span></span></span></span></span></span></span></span></span></span></span></p> <p> </p>
Figure 7 from: Li Y, Liu C, Lin L, Li Y, Xiao J, Loh K-H (2020) Pleistocene isolation caused by sea-level fluctuations shaped genetic characterization of Pampus minor over a large-scale geographical distribution. ZooKeys 969: 137-154. https://doi.org/10.3897/zookeys.969.52069
Figure 7 BSPs showing NefT (Nef = effective population size; T = generation time) changes over time for P. minor based on Cytb sequences. The upper and lower limits of the blue line represent the 95% confidence intervals of highest posterior densities (HPD) analysis. The solid black line represents median estimates of NefT.
Figure 5 from: Li Y, Liu C, Lin L, Li Y, Xiao J, Loh K-H (2020) Pleistocene isolation caused by sea-level fluctuations shaped genetic characterization of Pampus minor over a large-scale geographical distribution. ZooKeys 969: 137-154. https://doi.org/10.3897/zookeys.969.52069
Figure 5 Matrix of pairwise FST values between 11 P. minor populations based on Cytb sequences. * significant at p < 0.05 by the permutation test, ** extremely significant at p < 0.01 by the permutation test.
Figure 6 from: Li Y, Liu C, Lin L, Li Y, Xiao J, Loh K-H (2020) Pleistocene isolation caused by sea-level fluctuations shaped genetic characterization of Pampus minor over a large-scale geographical distribution. ZooKeys 969: 137-154. https://doi.org/10.3897/zookeys.969.52069
Figure 6 The expected mismatch distributions under a sudden expansion model (solid gray line) and the observed pairwise difference (black bars) of Cytb haplotypes of P. minor.
Figure 4 from: Li Y, Liu C, Lin L, Li Y, Xiao J, Loh K-H (2020) Pleistocene isolation caused by sea-level fluctuations shaped genetic characterization of Pampus minor over a large-scale geographical distribution. ZooKeys 969: 137-154. https://doi.org/10.3897/zookeys.969.52069
Figure 4 Unrooted minimum spanning tree showing the genetic relationships among the Cytb haplotypes of P. minor. Circle sizes are proportional to haplotype frequency. Perpendicular tick marks on the lines joining the haplotypes represent the number of nucleotide substitutions.
Figure 1 from: Li Y, Liu C, Lin L, Li Y, Xiao J, Loh K-H (2020) Pleistocene isolation caused by sea-level fluctuations shaped genetic characterization of Pampus minor over a large-scale geographical distribution. ZooKeys 969: 137-154. https://doi.org/10.3897/zookeys.969.52069
Figure 1 Sampling locations of P. minor. Populations are marked by abbreviations that correspond to Table 1.
Figure 2 from: Li Y, Liu C, Lin L, Li Y, Xiao J, Loh K-H (2020) Pleistocene isolation caused by sea-level fluctuations shaped genetic characterization of Pampus minor over a large-scale geographical distribution. ZooKeys 969: 137-154. https://doi.org/10.3897/zookeys.969.52069
Figure 2 Composition and distribution of 22 Cytb haplotypes in the Chinese and Malaysian populations.
Figure 3 from: Li Y, Liu C, Lin L, Li Y, Xiao J, Loh K-H (2020) Pleistocene isolation caused by sea-level fluctuations shaped genetic characterization of Pampus minor over a large-scale geographical distribution. ZooKeys 969: 137-154. https://doi.org/10.3897/zookeys.969.52069
Figure 3 NJ tree and distribution of Cytb haplotypes among populations for P. minor. Bootstrap supports of > 50 in 1000 replicates are shown.
Data from: Latitudinal variation of arrival and breeding phenology of the pied flycatcher Ficedula hypoleuca using large-scale citizen science data.
<p class="gmail-">Many species have advanced the timing of annual reproductive cycles in response to climatic warming, sometimes leading to asynchrony between trophic levels, with negative population consequences. Long-distance migratory birds, reliant on short seasonal food pulses for breeding, are considered particularly susceptible to such disjunction because late arrival may preclude optimal timing of egg-laying. It is unknown whether the relative timing of arrival and egg-laying is sufficiently plastic, in time and space, to enable an adaptive response when arrival times change relative to local food resources. We used citizen science data, describing pied flycatcher <i>Ficedula hypoleuca</i> arrival and egg-laying dates, to explore temporal (2013-2016) and spatial (across Great Britain) variation in the phenology of arrival, laying and their difference. To assess the long-term trend in arrival and laying at a single location, we used data from a long-term field study. The arrival-laying interval was consistently shorter in the north, driven by the contrast between spatial variation in arrival date and spatial invariance in laying date. To understand whether a short arrival-laying interval may have consequences for productivity, we assessed the association between this interval and clutch size. We found no statistically significant correlation between these two variables. To examine long-term changes in arrival and laying dates, we focussed on a single location in southwestern England. Both dates of first male arrival and first egg laid in a season advanced since 1986, with no evidence of interval shortening. Together, our results demonstrate spatial and annual variation in the arrival-laying interval, with no detected effect on fecundity. Thus, the interval from arrival to laying is likely dictated by spatially and temporally varying local conditions, suggesting these migrant birds may have the ability to adapt this interval to align with local conditions and mitigate potential mismatch impacts.</p>
Data from: Altitude shapes the environmental drivers of large-scale variation in abundance of a widespread mammal species
<p>Habitat quality and heterogeneity directly influence the distribution and abundance of organisms at different spatial scales. Determining the main environmental factors driving the variation in species abundance is crucial to understand the underlying ecological processes and this is especially important for widely distributed species living in contrasting environments. However, the responses to environmental variation are usually described at relatively small spatial scales. Here, we studied the variation in abundance of a widely distributed mustelid, the European badger (<i>Meles meles</i>), across France.<b> </b>We used (1) direct detections of 9,439 dead and living badgers, from 2006 to 2009, to estimate badger relative abundance in 703 small agricultural regions of metropolitan France and (2) a Bayesian modelling approach to identify the main environmental determinants influencing badger abundance.<b> </b>Despite a continuous distribution of badger in France, we found large variation in badger abundance between regions, explained by environmental factors. Among a set of 13 environmental variables, we demonstrated that badger abundance in lowlands (< 400 m a.s.l.) was mostly driven by biotic factors such as potential food resources (earthworm abundance and fruits crops) and forest fragmentation. Conversely, in mountainous areas, abiotic factors (i.e. soil texture and climate) drove the variation in badger relative abundance.<b> </b>These results underline the importance of mapping the abundance of wildlife species based on environmental suitability, and highlight the complexity of drivers influencing species abundance at such large spatial scales. Altitude shaped the environmental drivers (biotic <i>vs.</i> abiotic) that most influenced relative abundance of a widespread species. In the case of badger, such abundance maps are crucial to identify critical areas for species management as this mustelid is a main wild vector of bovine tuberculosis in several countries.</p>
Figure 8 from: Avila-Poveda OH (2020) Large-scale project 'Chiton of the Mexican Tropical Pacific': Chiton articulatus (Mollusca: Polyplacophora). Research Ideas and Outcomes 6: e60446. https://doi.org/10.3897/rio.6.e60446
Figure 8 Schematic diagram of the methodological process through which the chitons will pass to fulfil each of the proposed themes.
Figure 7 from: Avila-Poveda OH (2020) Large-scale project 'Chiton of the Mexican Tropical Pacific': Chiton articulatus (Mollusca: Polyplacophora). Research Ideas and Outcomes 6: e60446. https://doi.org/10.3897/rio.6.e60446
Figure 7 Group of volunteers and collaborators of the QUITÓN PROJECT in FACIMAR-UAS. The project has a logo registration (brand), which is used on the shirts. Shirts used in the field and presentations (congresses, workshops) are shown.
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.