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ShareScore release 0.9.0
Dataset results
93 results for “Assumption”
Data from: Detecting and quantifying introgression in hybridized populations: simplifying assumptions yield overconfidence and uncertainty
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Data from: No mutual mate choice for quality in zebra finches: time to question a widely-held assumption
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Testing assumptions of nitrogen cycling between a temperate, model coral host and its facultative symbiont: symbiotic contributions to dissolved inorganic nitrogen assimilation
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Data from: The mayfly nymph Austrophlebioides pusillus Harker defies common osmoregulatory assumptions
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Data from: Binary-state speciation and extinction method is conditionally robust to realistic violations of its assumptions
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Supplementary material: to support the assumption of no pore blocking and gel layer formation during filtration time (Separation of 5% (w/v) Prolastin)
<p>The data set is a part of the PhD thesis of Nattawan Chorhirankul, Wageningen University, The Netherlands.</p>
Impact of the Assumption in Charge of Medical Aid to the Procreation With Donation of Gametes on the Sexuality of the Couple
ClinicalTrials.gov study NCT03132818. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Distribution. Much of sub-Saharan Africa, from Senegal E to W Ethiopia and S Somalia, and S to NE Namibia and E South Africa, including Bioko, Principe, São Tomé, Annobón, and Unguja (Zanzibar Archipelago) Is; also in Madagascar, Aldabra, Assumption, Comoros (Mayotte I), Mauritius, and Réunion Is. in Emballonuridae
Distribution. Much of sub-Saharan Africa, from Senegal E to W Ethiopia and S Somalia, and S to NE Namibia and E South Africa, including Bioko, Principe, São Tomé, Annobón, and Unguja (Zanzibar Archipelago) Is; also in Madagascar, Aldabra, Assumption, Comoros (Mayotte I), Mauritius, and Réunion Is.
Differential expression analysis in single cell and spatial RNASeq without model assumptions
GEO Series GSE299816. Mus musculus. 1 samples. Type: Other.
Challenging the Traditional Dormancy Assumption: Antibiotic Persisters are Metabolically Active, Non-Growing Cells
GEO Series GSE278938. Escherichia coli. 12 samples. Type: Expression profiling by high throughput sequencing.
Dataset for the Paper: "Understanding Self-Claimed Assumptions in Deep Learning Frameworks: An Exploratory Study"
<p>This is the dataset for the paper: "Understanding Self-Claimed Assumptions in Deep Learning Frameworks: An Exploratory Study". It contains the 3004 Self-Claimed Assumptions (SCAs) extracted from nine deep learning frameworks (i.e., TensorFlow, Theano, PyTorch, Caffe, MXNet, Keras, CNTK, DL4J, and PaddlePaddle), which includes 2232 unique SCAs that have different content and 772 duplicated SCAs that have the same content as one of the 2232 SCAs.</p>
Dataset for the Paper: "Understanding Self-Claimed Assumptions in Deep Learning Frameworks: An Exploratory Study"
<p>This is the dataset for the paper: "Understanding Self-Claimed Assumptions in Deep Learning Frameworks: An Exploratory Study". It contains the 3084 Self-Claimed Assumptions (SCAs) extracted from nine deep learning frameworks (i.e., TensorFlow, Theano, PyTorch, Caffe, MXNet, Keras, CNTK, DL4J, and PaddlePaddle), which includes 2278 unique SCAs that have different content and 806 duplicated SCAs that have the same content as one of the 2278 SCAs.</p>
Database_ Exploring "Wear and Tear" of Joints and "Muscle Function" Assumptions in Skeletons with Known Occupation at Death
<p>This file contains the data used to explore the “Wear and Tear” of Joints and “Muscle Function” Assumptions in Skeletons with Known Occupation at Death.</p> <p>The manuscript has been published: <em>Alves-Cardoso, F., & Assis, S. (2021). Exploring “wear and tear” of joints and “muscle function” assumptions in skeletons with known occupation at death. American Journal of Physical Anthropology, 1–12. https://doi. org/10.1002/ajpa.24334</em></p> <p> </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.