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13,113 results for “Resistivity”
Data from: Macroevolutionary divergence along allometric lines of least resistance in frog hindlimb traits and its effect on locomotor evolution
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Recent fire history enhances semi-arid conifer forest drought resistance
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Host-enemy interactions provide limited biotic resistance for a range-expanding species via reduced apparent competition
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Phage selection drives resistance-virulence trade-offs in Ralstonia solanacearum plant pathogenic bacterium irrespective of the growth temperature
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Resistance and tolerance to imperfectly specialized parasites: Milkweed butterflies and their protozoan parasites
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Evolution along allometric lines of least resistance: Morphological differentiation in Pristurus geckos
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Data from: Beneficial reversal of dominance maintains a large-effect resistance polymorphism under fluctuating insecticide selection
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Can disease resistance evolve independently at different ages? Genetic variation in age-dependent resistance to disease in three wild plant species
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Whole-genome sequencing reveals asymmetric introgression between two sister species of cold-resistant leaf beetles
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Dataset for: The redlegged earth mite draft genome provides new insights into pesticide resistance evolution and demography in its invasive Australian range
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Data for: Microbe-induced plant resistance alters aphid inter-genotypic competition leading to rapid evolution with consequences for plant growth and aphid abundance
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SBC LTER: REEF: Data to support "Niche Complementarity and Resistance to Grazing Promote the Invasion Success of Sargassum horneri in North America"
These data describe the results of surveys and manipulative experiments performed to investigate how niche complementarity, competition, and herbivory influence the success of the invasive seaweed Sargassum horneri. This data package includes five data tables and they are used to support the manuscript: Marks LM, Reed DC, Holbrook SJ (2020) Niche Complementarity and Resistance to Grazing Promote the Invasion Success of Sargassum horneri in North America. Diversity, 12(2)
A 3D resistivity model of the Acoculco high temperature geothermal system, Mexico
<p>The dataset is the final three-dimensional resistivity model of the high temperature geothermal field Acoculco, in Mexico.</p> <p>The model is described in deliverable 5.2 of the GEMex Project, funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 727550, and by the Mexican Energy Sustainability Fund<br> CONACYT-SENER, Project 2015-04-268074.</p>
Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics
<p>Datasets for manuscript "Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics"</p> <p><strong>Metadata.zip</strong></p> <ol> <li><strong>phenotypes.txt: </strong>tabular file containing binary resistance phenotypes based on CLSI guidelines, where the rows are the isolates and the columns correspond to different drugs. Resistance : 1, susceptibility: 0, missing: intermediate resistant</li> </ol> <p><strong>Features_gpa_exp_snps.zip </strong></p> <p>We provide the processed molecular data as Numpy compressed files (npz.). You can use the Numpy load method to read in these tables https://docs.scipy.org/doc/numpy/reference/generated/numpy.load.htm. The row (strains_list) and column labels (feature_lists) are stored separately.</p> <ol> <li><strong>genexp</strong>: gene expression table directory <ul> <li>genexp_feature_vect.npz: The feature matrix in the numpy format</li> <li>genexp_feature_list.txt: The columns of the feature matrix (features)</li> <li>genexp_strains_list.txt: The rows of the feature matrix (isolates)</li> </ul> </li> <li><strong>gpa: </strong>gene presence/absence table directory <ul> <li>gpa_feature_vect.npz: The feature matrix in the numpy format</li> <li>gpa_feature_list.txt: The columns of the feature matrix (features)</li> <li>gpa_strains_list.txt: The rows of the feature matrix (isolates)</li> </ul> </li> <li><strong>snps: </strong>SNPs table directory <ul> <li>snps_feature_vect.npz: The feature matrix in the numpy format</li> <li>snps_feature_list.txt: The columns of the feature matrix (features)</li> <li>snps_strains_list.txt: The rows of the feature matrix (isolates)</li> </ul> </li> </ol>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Ireland
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_IE_20200204: >> The Food Safety Authority of Ireland</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Sweden
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_SE_20200204: >> National Veterinary Institute, Swedish Zoonosis Centre</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Latvia
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_LV_20200204: >> Assessment and Registration Agency of Food and Veterinary Service of Latvia</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Spain
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_ES_20200204: >> Agencia Espaola de Consumo, Seguridad Alimentaria y Nutricin >> Ministerio de Agricultura, Pesca y Alimentacin</p>
Specific monitoring results of ESBL-/AmpC-/carbapenemase-producing bacteria and specific monitoring of carbapenemase-producing bacteria, in the absence of isolates detected complementing the European Union Overview Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2017/2018
<p>This dataset derives from the specific monitoring of E. coli producers of ESBLs/AmpC/carbapenemases, as well as the specific monitoring of carbapenemase-producers (voluntary reporting), in the absence of any isolates detected. This dataset contains only data when Total units positive equals zero '0'.</p>
Antimicrobial resistance monitoring results complementing the EU Overview Summary Report on AMR in zoonotic and indicator bacteria from humans, animals and food in 2017/2018 - Cyprus
<p>This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision 2013/652/EU. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision 2013/652/EU. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: AMR_2018_CY_20200204: >> Ministry of Agriculture, Natural Resources and Evironment - Veterinary Services</p>
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.