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167 results for “Identifier mapping”
Figure 15. Scelidosaurus. The principal jaw adductor muscles identified. A, dorsal muscle origin map. B–D in Scelidosaurus harrisonii (Dinosauria: Ornithischia) from the Early Jurassic of Dorset, England: biology and phylogenetic relationships
Figure 15. Scelidosaurus. The principal jaw adductor muscles identified. A, dorsal muscle origin map. B–D, muscle reconstructions. Abbreviations: AN.OR, m. anguli oris; bod, bodenaponeurosis; MAMEM, m. adductor mandibulae externus medialis; MAMEP, profundus; MAMES, superficialis; MAMP, posterior; MLPt, levator pterygoideus; MPST, pseudotemporalis; MPT, pterygoideus.
Fragment Hotspot Mapping to Identify Selectivity-Determining Regions between Related Proteins - Case Studies
<p>Dataset and scripts accompanying the publication "Fragment Hotspot Mapping to Identify Selectivity-Determining Regions between Related Proteins"</p>
FIGURE1. Map showing the sampling localities and distribution of all valid Korean species identified and described so far. The black line between Stations 6a and 6b represents a man-made road with no gap for water entry from either side. Stations 1 to 15 refer to the study sites in Vakati et al. (2019), station 16 refers to the study site in Kim et al. (2017). in -On- two- new- species- of- Nannopus- Brady,- 1880- (Copepoda:- Harpacticoida Nannopodidae)-from-intertidal-mudflats-of-the-Korean-west-coast-(Yellow-Sea)
FIGURE1. Map showing the sampling localities and distribution of all valid Korean species identified and described so far. The black line between Stations 6a and 6b represents a man-made road with no gap for water entry from either side. Stations 1 to 15 refer to the study sites in Vakati et al. (2019), station 16 refers to the study site in Kim et al. (2017).
BridgeDb Complex Identifier Mapping Database
<p>BridgeDb identifier mapping databases for complexes extracted from Wikidata. Code to generate the database (https://github.com/bridgedb/Wikidata2Bridgedb - ComplexIdentifiers.java). </p>
BridgeDb: pathway identifier mapping database derived from Wikidata
<p>Release of a BridgeDb gene identifier mapping database between Wikidata and Ensembl.</p> <pre>[INFO]: Database finished. INFO: old database is Wikidata 1.0.0 (build: 20230506) INFO: new database is Wikidata 1.0.0 (build: 20230506) INFO: Number of ids in Wd (Wikidata): 153715 (unchanged) INFO: Number of ids in En (Ensembl): 153637 (unchanged) INFO: new size is 95 Mb (changed +0.0%) INFO: total number of identifiers is 307352 INFO: total number of mappings is 307430 </pre>
Data from: Admixture mapping identifies introgressed genomic regions in North American canids
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Data from: QTL mapping identifies candidate alleles involved in adaptive introgression and range expansion in a wild sunflower
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Data from: Proteomic analysis of barley mapping population subjected to drought identifies proteins with genotype×environment interaction and pQTLs
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High spatial resolution mapping identifies habitat characteristics of the invasive vine Antigonon leptopus on St. Eustatius (Lesser Antilles)
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Data from: Admixture mapping in two Mexican samples identifies significant associations of locus ancestry with triglyceride levels in the BUD13/ZNF259/APOA5 region and fine mapping points to rs964184 as the main driver of the association signal
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Data from: Genome-wide association and regional heritability mapping to identify loci underlying variation in nematode resistance and body weight in Scottish Blackface lambs
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Data from: A novel resistance gene for bacterial blight in rice, Xa43(t) identified by GWAS and confirmed by QTL mapping using a bi-parental population
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The Threatened Species No-Go Mapping Tool: An online open-access land-use decision support tool that identifies areas of importance for highly sensitive species of conservation concern
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Data from: Genetic mapping identifies a major locus spanning P450 clusters associated with pyrethroid resistance in kdr-free Anopheles arabiensis from Chad
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Combining genome-wide studies of breast, prostate, ovarian and endometrial cancers maps cross-cancer susceptibility loci and identifies new genetic associations
<p>Data set linked to the paper, "Combining genome-wide studies of breast, prostate, ovarian and endometrial cancers maps cross-cancer susceptibility loci and identifies new genetic associations". Pre-print of the paper is here: <a href="https://doi.org/10.1101/2020.06.16.146803">https://doi.org/10.1101/2020.06.16.146803</a>.</p> <p> </p> <p>cross_cancer_sum_stats.txt.gz contains summary genome-wide association statistics for susceptibility to single cancers (breast (BR), prostate (PR), ovarian (OV), endometrial (EN), estrogen receptor (ER)-positive breast (POS), ER-negative breast (NEG), and high-grade serous ovarian (HGS) cancers) and from the cross-cancer meta-analysis (main [main] and subtype-focused [sub]). EA in the header refers to the effect allele, OA is the other allele, EAF is the effect allele frequency in the largest of the single cancer data sets (BR), IMPR2 is the imputation quality in the largest of the single cancer data sets (BR), SE is the standard error, PVAL is the P-value, RE2Cs1 is the RE2C statistic mean effect part, RE2Cs2 is the RE2C statistic heterogeneity part, RE2Cp* is the RE2C* P-value. More on RE2Cp* can be found here: <a href="http://software.buhmhan.com/RE2C/index.php?mid=contact&act=dispBoardWrite">http://software.buhmhan.com/RE2C/index.php?mid=contact&act=dispBoardWrite</a> and in <a href="https://academic.oup.com/bioinformatics/article/33/14/i379/3953957">https://academic.oup.com/bioinformatics/article/33/14/i379/3953957</a> SNP names in cross_cancer_sum_stats.txt.gz include the chromosome and build 37 position.</p> <p> </p> <p>main_tetrachoric_corr_matrix.txt and subtype_tetrachoric_corr_matrix.txt provide the tetrachoric correlation matrices used in the main and subtype-focused meta-analyses. These were also used to specify the cryptic.cor argument of the exh.abf function of MetABF. More on MetABF can be found here: <a href="https://github.com/trochet/metabf">https://github.com/trochet/metabf</a> and in <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/gepi.22202">https://onlinelibrary.wiley.com/doi/abs/10.1002/gepi.22202</a></p> <p> </p> <p>prior_sigmas_for_metabf.txt contains the values used to specify the prior.sigma argument of the exh.abf function in MetABF.</p> <p> </p> <p>The breast cancer data used are described in <a href="https://pubmed.ncbi.nlm.nih.gov/29059683/"><strong>PMID 29059683</strong></a> and can be downloaded from <a href="http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/oncoarray-and-combined-summary-result/gwas- summary-results-breast-cancer-risk-2017/">http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/oncoarray-and-combined-summary-result/gwas- summary-results-breast-cancer-risk-2017/</a> (this link also includes acknowledgements). The prostate cancer data are described in <a href="https://pubmed.ncbi.nlm.nih.gov/29892016/"><strong>PMID 29892016</strong></a> and can be downloaded from: <a href="http://practical.icr.ac.uk/blog/?page_id=8164">http://practical.icr.ac.uk/blog/?page_id=8164</a> (this link also includes acknowledgements). The ovarian cancer data used are described in <a href="https://pubmed.ncbi.nlm.nih.gov/28346442/"><strong>PMID 28346442</strong></a> and can be downloaded from <a href="https://www.ebi.ac.uk/gwas/studies/GCST004415">https://www.ebi.ac.uk/gwas/studies/GCST004415</a>. The endometrial cancer data are described in <a href="https://pubmed.ncbi.nlm.nih.gov/30093612/"><strong>PMID 30093612</strong></a> and can be downloaded from <a href="https://www.ebi.ac.uk/gwas/studies/GCST006464">https://www.ebi.ac.uk/gwas/studies/GCST006464</a>. These links point to the same data that form the basis of the cross_cancer_sum_stats.txt.gz file.</p> <p> </p> <p><strong>The sample size and precision of the data presented should preclude identification of any individual study participant. However, in downloading these data, you undertake not to attempt to identify individual study participant and not to re-post these data to a third-party website. Please cite the PMIDs highlighted above along with the appropriate acknowledements if you use the cross_cancer_sum_stats.txt.gz file.</strong></p> <p> </p> <p>If you have any questions about this repository, please email Siddhartha Kar at siddhartha dot kar at bristol dot ac dot uk</p>
Identifying and mapping the different ecosystem services around Mosvatnet from the 1930s until present day
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Dataset Characterizing Architectural Evaluations and Identifying Quality Attributes addressed in Systems-of-Systems: A Systematic Mapping Study
<p>Dataset</p>
Appendix Characterizing Architectural Evaluations and Identifying Quality Attributes addressed in Systems-of-Systems: A Systematic Mapping Study
<p>Data analysis.</p>
Systematic Mapping Appendix - Identifying approaches to generate test cases in model-based testing: a
<p>The appendix present the complete mapping of individual studies and its categories.</p>
Data from: Genetic mapping of molar size relations identifies inhibitory locus for third molars in mice
Molar size in Mammals shows considerable disparity and exhibits variation similar to that predicted by the Inhibitory Cascade model. The importance of such developmental systems in favoring evolutionary trajectories is also underlined by the fact that this model can predict macroevolutionary patterns. Using backcross mice, we mapped QTL for molar sizes controlling for their sequential development. Genetic controls for upper and lower molars appear somewhat similar, and regions containing genes implied in dental defects drive this variation. We mapped three relationship QTLs (rQTL) modifying the control of the mesial molars on the focal third molar. These regions overlap Shh, Sostdc1 and Fst genes, which have pervasive roles in development and should be buffered against new variation. It has theoretically been shown that rQTL produces new variation channeled in the direction of adaptive changes. Our results provide evidence that evolutionary/disease patterns of tooth size variation could result from such a non-random generating process.
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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.
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.