Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
11,177
datasets available to search
ShareScore release 0.9.0
Dataset results
11,177 results for “identify”
Figure 1a from: Qiao G, WANG J, Jiang L (2011) Use of a mitochondrial COI sequence to identify species of the subtribe Aphidina (Hemiptera, Aphididae). ZooKeys 122: 1-17. https://doi.org/10.3897/zookeys.122.1256
Figure 1a - Neighbor-joining analysis of 198 specimens. It was based on COI sequence divergence in 591 bp of the COI gene using Kimura's two parameter model.
Figure 1d from: Qiao G, WANG J, Jiang L (2011) Use of a mitochondrial COI sequence to identify species of the subtribe Aphidina (Hemiptera, Aphididae). ZooKeys 122: 1-17. https://doi.org/10.3897/zookeys.122.1256
Figure 1d - Neighbor-joining analysis of 198 specimens. It was based on COI sequence divergence in 591 bp of the COI gene using Kimura's two parameter model.
Figure 1c from: Qiao G, WANG J, Jiang L (2011) Use of a mitochondrial COI sequence to identify species of the subtribe Aphidina (Hemiptera, Aphididae). ZooKeys 122: 1-17. https://doi.org/10.3897/zookeys.122.1256
Figure 1c - Neighbor-joining analysis of 198 specimens. It was based on COI sequence divergence in 591 bp of the COI gene using Kimura's two parameter model.
Figure 1b from: Qiao G, WANG J, Jiang L (2011) Use of a mitochondrial COI sequence to identify species of the subtribe Aphidina (Hemiptera, Aphididae). ZooKeys 122: 1-17. https://doi.org/10.3897/zookeys.122.1256
Figure 1b - Neighbor-joining analysis of 198 specimens. It was based on COI sequence divergence in 591 bp of the COI gene using Kimura's two parameter model. * They were originally misidentified as Aphis asclepiadis Fitch; actually, should be Aphis nerii Boyer de Fonscolombe.
Figure 1 from: Cox K, Thomaes A, Antonini G, Zilioli M, De Gelas K, Harvey D, Solano E, Audisio P, McKeown N, Shaw P, Minetti R, Bartolozzi L, Mergeay J (2013) Testing the performance of a fragment of the COI gene to identify western Palaearctic stag beetle species (Coleoptera, Lucanidae). ZooKeys 365: 105-126. https://doi.org/10.3897/zookeys.365.5526
Figure 1 - Bootstrap consensus NJ tree inferred from 10 000 replicates, with a cut off value of 70%, based on K2P-distances between 60 haplotypes of the 3' end of the COI gene.
Figure 3 from: Stahls G, Laiho J (2013) DNA barcodes identify Central-Asian Colias butterflies (Lepidoptera, Pieridae). ZooKeys 365: 175-196. https://doi.org/10.3897/zookeys.365.5879
Figure 3 - Neighbour-Joining tree using the Tamura-Nei model with gamma distributed rates for the RpS2 sequences.
Figure 2 from: Mankga L, Kowiyou Y, Moteetee A, Daru B, van der Bank M (2013) Efficacy of the core DNA barcodes in identifying processed and poorly conserved plant materials commonly used in South African traditional medicine. ZooKeys 365: 215-233. https://doi.org/10.3897/zookeys.365.5730
Figure 2 - Evaluation of barcode gaps in matK, rbcLa and rbcLa + matK for commonly used medicinal plants of South Africa. A Boxplots indicate the genetic variation between interspecific distance and intraspecific distance; the boxplots clearly shows significant differences between inter- and intraspecific distances for all gene regions tested (P < 0.001; see text) B Lineplot of the barcode gap for the commonly used plants in South African medicine. For each gene region, the grey lines correspond to the furthest intraspecific distance (bottom of line value), and the closest interspecific distance (top of line value). The red lines show where this relationship is reversed, i.e. cases where there is no barcode gap.
Figure 1 from: Mankga L, Kowiyou Y, Moteetee A, Daru B, van der Bank M (2013) Efficacy of the core DNA barcodes in identifying processed and poorly conserved plant materials commonly used in South African traditional medicine. ZooKeys 365: 215-233. https://doi.org/10.3897/zookeys.365.5730
Figure 1 - Examples ofmedicinal herbs bought at Faraday muthi market in Johannesburg A different medicinal herbs in bags B Seeds of Entada rheedii (tindili) C mixed herbs (fembo) D A twig of Adenia gummifera (mphinde umshaye) E Barks of Vachellia sp. (umkhanya-kute) F Bulb of Boophane disticha (umqotho) G mixed herbs H Myrothamnus flabellifolius (vuka) I Barks of Vachellia sp. (umkhanya-kute) J Sarcostemma viminale (ube nam) K Plant of Clivia sp. (mayime) L Stangeria eriopus (imfingo) M mixed herbs (isihlalakahle) N Tuber (umbonsi) O Helichrysum sp. (impepo) and P Twigs of Synadenium cupulare (umdletshane). Names in brackets are vernacular names in isiZulu.
Figure 3 from: Guralnick RP, Cellinese N, Deck J, Pyle RL, Kunze J, Penev L, Walls R, Hagedorn G, Agosti D, Wieczorek J, Catapano T, Page EDM (2015) Community Next Steps for Making Globally Unique Identifiers Work for Biocollections Data. ZooKeys 494: 133-154. https://doi.org/10.3897/zookeys.494.9352
Figure 3 - Identifier schemes differ in whether redirections and mappings to ensure stability are centrally managed or not. Top: a DOI dereferencing service like CrossRef or Datacite redirects to the actual content provider; the URIs of content data and RDF metadata are publicly visible and can be used as independent (albeit often unstable) identifiers. Bottom: A linked open data pattern, where each content provider assumes the responsibility for maintaining a stable mapping; the content negotiation is internal. Modified after Hagedorn 2013.
Figure 2 from: Guralnick RP, Cellinese N, Deck J, Pyle RL, Kunze J, Penev L, Walls R, Hagedorn G, Agosti D, Wieczorek J, Catapano T, Page EDM (2015) Community Next Steps for Making Globally Unique Identifiers Work for Biocollections Data. ZooKeys 494: 133-154. https://doi.org/10.3897/zookeys.494.9352
Figure 2 - Example of a PURL-URI as a QR-Code, in this example attached to a digitised lichen type specimen in the Natural History Museum, University of Oslo. The QR-Code corresponds to http://purl.org/nhmuio/id/c1a8b878-a4f9-448b-be00-26cbad58b11c.
Figure 1 from: Guralnick RP, Cellinese N, Deck J, Pyle RL, Kunze J, Penev L, Walls R, Hagedorn G, Agosti D, Wieczorek J, Catapano T, Page EDM (2015) Community Next Steps for Making Globally Unique Identifiers Work for Biocollections Data. ZooKeys 494: 133-154. https://doi.org/10.3897/zookeys.494.9352
Figure 1 - Example of UUIDs embedded within QR-Codes on microcentrifuge tube labels. The 5 mm × 5 mm QR-Codes (Version 2) are printed with a standard laser printer on sheets of self-adhesive 9 mm dots, and scan reliably with a standard barcode reader, while still providing room for a human-readable 5-character prefix + 5-digit number (the human-readable number and UUID are permanently cross-linked in the data management system). Photo: Robert K. Whitton.
Immunomics datasets: to identify potential candidates for chimeric vaccine design to cervix papilloma
<p>Immunomics datasets: to identify potential candidates for chimeric vaccine design to cervix papilloma</p>
EEG p-adic quantum potential accurately identifies depression, schizophrenia and cognitive decline
<p>No diagnostic or predictive instruments to help with early diagnosis and timely therapeutic intervention are available as yet for most neuro-psychiatric disorders. A quantum potential mean and variability score (qpmvs), to identify neuropsychiatric and neurocognitive disorders with high accuracy, based on routine EEG recordings, was developed. Information processing in the brain is assumed to involve integration of neuronal activity in various areas of the brain. Thus, the presumed quantum-like structure allows quantification of connectivity as a function of space and time (locality) as well as of instantaneous quantum-like effects in information space (non-locality). EEG signals reflect the holistic (nonseparable) function of the brain, including the highly ordered hierarchy of the brain, expressed by the quantum potential according to Bohmian mechanics, combined with dendrogram representation of data and p-adic numbers. Participants consisted of 230 participants including 28 with major depression, 42 with schizophrenia, 65 with cognitive impairment, and 95 controls. Routine EEG recordings were used for the calculation of qpmvs based on ultrametric analyses, closely coupled with p-adic numbers and quantum theory. Based on area under the curve, high accuracy was obtained in separating healthy controls from those diagnosed with schizophrenia (p<0.0001), depression (p<0.0001), Alzheimer's disease (AD; p<0.0001), and mild cognitive impairment (MCI; p<0.0001) as well as in differentiating participants with schizophrenia from those with depression (p<0.0001), AD (p<0.0001) or MCI (p<0.0001) and in differentiating people with depression from those with AD (p<0.0001) or MCI (p<0.0001). The novel EEG analytic algorithm (qpmvs) seems to be a useful and sufficiently accurate tool for diagnosis of neuropsychiatric and neurocognitive diseases and may be able to predict disease course and response to treatment.</p>
Supplementary material 1 from: Agosti D, Benichou L, Addink W, Arvanitidis C, Catapano T, Cochrane G, Dillen M, Döring M, Georgiev T, Gérard I, Groom Q, Kishor P, Kroh A, Kvaček J, Mergen P, Mietchen D, Pauperio J, Sautter G, Penev L (2022) Recommendations for use of annotations and persistent identifiers in taxonomy and biodiversity publishing. Research Ideas and Outcomes 8: e97374. https://doi.org/10.3897/rio.8.e97374
Overview table of recommendations
De-identified article and author characteristics for a large data set of Web of Science
<p>This data set contains article and author characteristics for all records in the Web of Science, 2000-2020. Standard article identifiers have been removed and replaced with a document ID (`doc_id`), as linking to the original ID is not permitted.</p>
Integrative single-cell analysis of cardiogenesis identifies developmental trajectories and non-coding mutations in congenital heart disease (Invitro ArchR Object)
<p>This repo contains invitro ArchR object</p>
Integrative single-cell analysis of cardiogenesis identifies developmental trajectories and non-coding mutations in congenital heart disease (Invivo ArchR Object)
<p>This repo contains invivo ArchR object</p>
Figure 1 in Reviewing the status and demise of the Endangered Eld's deer and identifying priority sites and conservation actions in Cambodia
Figure 1: Map of protected areas in Cambodia.
Imaging-based screening identifies modulators of the eIF3 translation initiation factor complex in Candida albicans
<p>Fungal pathogens like Candida albicans can cause devastating human disease. Treatment of candidemia is complicated by the high rate of resistance to common antifungal therapies. Additionally, there is host toxicity associated with many antifungal compounds due to the conservation between essential mammalian and fungal proteins. An attractive new approach for antimicrobial development is to target virulence factors: non-essential processes that are required for the organism to cause disease in human hosts. This approach expands the potential target space while reducing the selective pressure towards resistance, as these targets are not essential for viability. In C. albicans, a key virulence factor is the ability to transition to hyphal morphology. We developed a high-throughput image analysis pipeline to distinguish between yeast and filamentous growth in C. albicans at the single cell level. Based on this phenotypic assay, we screened the FDA drug repurposing library of 2,017 compounds for their ability to inhibit filamentation and identified 33 compounds that block the hyphal transition in C. albicans with IC50 values ranging from 0.2 to 150 µM. Multiple compounds showed a phenyl vinyl sulfone chemotype, prompting further analysis. Of these phenyl vinyl sulfones, NSC 697923 displayed the most efficacy, and by selecting for resistant mutants, we identified eIF3 as the target of NSC 697923 in C. albicans. </p>
Natural history specimens collected and/or identified and deposited.
Natural history specimen data collected and/or identified by Fanny Tello Ramos, <a href="https://orcid.org/0009-0007-3996-683X">https://orcid.org/0009-0007-3996-683X</a>. Claims were made on Bionomia, <a href="http://bionomia.net">https://bionomia.net</a> using specimen data from the Global Biodiversity Information Facility, <a href="https://gbif.org">https://gbif.org</a>.
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.