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.
4,144
datasets available to search
ShareScore release 0.9.0
Dataset results
4,144 results for “ITS barcode”
Figure 2 from: Mulcahy DG, Lee JL, Miller AH, Chand M, Thura MK, Zug GR (2018) Filling the BINs of life: Report of an amphibian and reptile survey of the Tanintharyi (Tenasserim) Region of Myanmar, with DNA barcode data. ZooKeys 757: 85-152. https://doi.org/10.3897/zookeys.757.24453
Figure 2 Combined (16S and COI) Neighbor-joining tree for all specimens sequenced in this study.
Figure 2 from: Raupach MJ, Hannig K, Morinière J, Hendrich L (2018) A DNA barcode library for ground beetles of Germany: the genus Amara Bonelli, 1810 (Insecta, Coleoptera, Carabidae). ZooKeys 759: 57-80. https://doi.org/10.3897/zookeys.759.24129
Figure 2 - Continue.
Figure 4 from: Constantinescu IC, Popa OP, Popa LO, Cobzaru I, Khlur B MD, Adam C (2018) A new feather mite species of the genus Trouessartia Canestrini, 1899 (Acarina, Trouessartiidae) – an integrative description (morphology and DNA barcoding data). ZooKeys 789: 19-35. https://doi.org/10.3897/zookeys.789.27829
Figure 4 Trouessartianiltavae Constantinescu, sp. n., female paratype: dorsal view of idiosoma.
Figure 2 from: Constantinescu IC, Popa OP, Popa LO, Cobzaru I, Khlur B MD, Adam C (2018) A new feather mite species of the genus Trouessartia Canestrini, 1899 (Acarina, Trouessartiidae) – an integrative description (morphology and DNA barcoding data). ZooKeys 789: 19-35. https://doi.org/10.3897/zookeys.789.27829
Figure 2 Trouessartianiltavae Constantinescu, sp. n., male holotype: ventral view of idiosoma.
Figure 1 from: Constantinescu IC, Popa OP, Popa LO, Cobzaru I, Khlur B MD, Adam C (2018) A new feather mite species of the genus Trouessartia Canestrini, 1899 (Acarina, Trouessartiidae) – an integrative description (morphology and DNA barcoding data). ZooKeys 789: 19-35. https://doi.org/10.3897/zookeys.789.27829
Figure 1 Trouessartianiltavae Constantinescu, sp. n., male holotype: dorsal view of idiosoma.
Figure 5 from: Constantinescu IC, Popa OP, Popa LO, Cobzaru I, Khlur B MD, Adam C (2018) A new feather mite species of the genus Trouessartia Canestrini, 1899 (Acarina, Trouessartiidae) – an integrative description (morphology and DNA barcoding data). ZooKeys 789: 19-35. https://doi.org/10.3897/zookeys.789.27829
Figure 5 Trouessartianiltavae Constantinescu, sp. n., female paratype: ventral view of idiosoma.
Figure 10 from: Motamedinia B, Skevington JH, Kelso S (2019) Revision of Claraeola (Diptera, Pipunculidae) in the Middle East based on morphology and DNA barcodes. ZooKeys 873: 85-111. https://doi.org/10.3897/zookeys.873.36645
Figure 10 Claraeola species distribution in the Middle East.
Figure 1 from: Zhang H, Zhang Y, Duan Y (2019) DNA barcoding of Deltocephalus Burmeister leafhoppers (Cicadellidae, Deltocephalinae, Deltocephalini) in China. ZooKeys 867: 55-71. https://doi.org/10.3897/zookeys.867.35058
Figure 1 Distribution of Deltocephalus in China, codes same as in Table 1.
Figure 1 from: Siddiqui JA, Chen Z, Li Q, Deng J, Lin X, Huang X (2019) DNA barcoding of aphid-associated ants (Hymenoptera, Formicidae) in a subtropical area of southern China. ZooKeys 879: 117-136. https://doi.org/10.3897/zookeys.879.29705
Figure 1 Map of Fujian Province showing the sampling sites.
Figure 6 from: Özcan T (2019) Defining phylogenetic relationship of Nepeta x tmolea and its parents via DNA barcoding. PhytoKeys 134: 83-96. https://doi.org/10.3897/phytokeys.134.38238
Figure 6 Insertions, deletions and single nucleotide polymorphisms based on trnL-F sequences.
Figure 5 from: Özcan T (2019) Defining phylogenetic relationship of Nepeta x tmolea and its parents via DNA barcoding. PhytoKeys 134: 83-96. https://doi.org/10.3897/phytokeys.134.38238
Figure 5 Insertions, deletions and single nucleotide polymorphisms based on rpl32-trnL sequences.
Figure 4 from: Özcan T (2019) Defining phylogenetic relationship of Nepeta x tmolea and its parents via DNA barcoding. PhytoKeys 134: 83-96. https://doi.org/10.3897/phytokeys.134.38238
Figure 4 Dendroscope cladogram and PCA diagram based on rpl32-trnL data.
Figure 1 in Endogean beetles (Coleoptera) of illustrated DNA barcode library Guatemala: deep soil sampling and
Figure 1. Map of the southern part of Guatemala showing the localities of the 26 deep soil samples.
Figure 3 in First record of the schizomid Stenochrus portoricensis (Schizomida: Hubbardiidae) in Poland, with DNA barcode data
Figure 3. Flagellum of Stenochrus portoricensis.
Figure 1 in First record of the schizomid Stenochrus portoricensis (Schizomida: Hubbardiidae) in Poland, with DNA barcode data
Figure 1. Stenochrus portoricensis dorsal view.
Figure 3 in Report on Sicklefin weasel shark Hemigaleus microstoma (Bleeker, 1852) (Carcharhiniformes: Hemigaleidae) from the Andaman Islands, Indian EEZ with DNA barcodes
Figure 3. Hemigaleus microstoma ventral view of the head, 610 mm TL female.
Data from: ITS1: a DNA barcode better than ITS2 in eukaryotes?
A DNA barcode is a short piece of DNA sequence used for species determination and discovery. The internal transcribed spacer (ITS/ITS2) region has been proposed as the standard DNA barcode for fungi and seed plants, and has been widely used in DNA barcoding analyses for other biological groups, e.g. algae, protists, and animals. The ITS region consists of both ITS1 and ITS2 regions. Here, a large scale meta-analysis was carried out to compare ITS1 and ITS2 from three aspects: PCR amplification, DNA sequencing and species discrimination, in terms of the presence of DNA barcoding gaps, species discrimination efficiency, sequence length distribution, GC content distribution and primer universality. In total, 85,345 sequence pairs in ten major groups of eukaryotes, including ascomycetes, basidiomycetes, liverworts, mosses, ferns, gymnosperms, monocotyledons, eudicotyledons, insects, and fishes, covering 611 families, 3,694 genera, and 19,060 species, were analyzed. Using similarity-based methods, we calculated species discrimination efficiencies for ITS1 and ITS2 in all major groups, families, and genera. Using Fisher's exact test, we found that ITS1 has significantly higher efficiencies than ITS2 in 17 of the 47 families and 20 of the 49 genera, which are sample-rich. By in silico PCR amplification evaluation, primer universality of the extensively applied ITS1 primers was found superior to that of ITS2 primers. Additionally, shorter length of amplification product and lower GC content were discovered to be two other advantages of ITS1 for sequencing. In summary, ITS1 represents a better DNA barcode than ITS2 for eukaryotic species.
Data from: DNA barcoding of invasive plants in China: a resource for identifying invasive plants
Invasive plants have aroused attention globally for causing ecological damage and having a negative impact on the economy and human health. However, it can be extremely challenging to rapidly and accurately identify invasive plants based on morphology because they are an assemblage of many different families and many plant materials lack sufficient diagnostic characteristics during border inspections. It is therefore urgent to evaluate candidate loci and build a reliable genetic library to prevent invasive plants from entering China. In this study, five common single markers (ITS, ITS2, matK, rbcL and trnH-psbA) were evaluated using 634 species (including 469 invasive plant species in China, 10 new records to China, 16 potentially invasive plant species around the world but not introduced into China yet and 139 plant species native to China) based on three different methods. Our results indicated that ITS2 displayed largest intra- and interspecific divergence (1.72% and 91.46%). Based on NJ tree method, ITS2, ITS, matK, rbcL and trnH-psbA provided 76.84%, 76.5%, 63.21%, 52.86% and 50.68% discrimination rates, respectively. The combination of ITS+matK performed best and provided 91.03% discriminatory power, followed by ITS2+matK (85.78%). For identifying unknown individuals, ITS+matK had 100% correct identification rate based on our database, followed by ITS/ITS2 (both 93.33%) and ITS2+matK (91.67%). Thus, we propose ITS/ITS2+matK as the most suitable barcode for invasive plants in China. This study also demonstrated that DNA barcoding is an efficient tool for identifying invasive species.
Data from: DNA barcoding gap: reliable species identification over morphological and geographical scales
The philosophical basis, and utility of DNA barcoding has been a subject of numerous debates. While most literature embraces it, some studies continue to question its use in dipterans, butterflies, and marine gastropods. Here, we explore the utility of DNA barcoding in identifying spider species that vary in taxonomic affiliation, morphological diagnosibility and geographic distribution. Our first test searched for a "barcoding gap" by comparing intra- and interspecific means, medians and overlap in more than 75,000 computed Kimura 2 parameter (K2P) genetic distances in three families. Our second test compared K2P distances of congeneric species with high versus low morphological distinctness in 20 genera of 11 families. Our third test explored the effect of enlarging geographical sampling area at a continental scale on genetic variability in DNA barcodes within 20 species of nine families. Our results generally point towards a high utility of DNA barcodes in identifying spider species. However, the size of the barcoding gap strongly depends on taxonomic groups and practices. It is becoming critical to define the barcoding gap statistically more consistently, and to document its variation over taxonomic scales. Our results support models of independent patterns of morphological and molecular evolution by showing that DNA barcodes are effective in species identification regardless of their morphological diagnosibility. We also show that DNA barcodes represent an effective tool for identifying spider species over geographic scales, yet their variation contains useful biogeographic information.
Fig. 14 in NGS-barcodes, haplotype networks combined to external morphology help to identify new species in the mangrove genus Ngirhaphium Evenhuis & Grootaert, 2002 (Diptera: Dolichopodidae: Rhaphiinae) in Southeast Asia
Fig. 14. Maximum likelihood tree of Ngirhaphium based on NGS barcodes (COI, 313bp).
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.