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 2. A in Description and taxonomic analysis of a tuberculated turtle leech from the Outer Banks, North Carolina, USA, provisionally identified as Placobdella multilineata Moore, 1953 (Hirudinea: Glossiphoniidae)
FIGURE 2. A, Typical swamp habitat for the Albemarle turtle leech. Shown is Griffin Swamp, Pasquotank County, NC, where 8 specimens (4.5–44 mm) were collected overnight by means of the 'Essig' leech trap shown in B (see Methods). B, This pocketed, aluminium device transforms sampling leeches in such inhospitable swamps. Scale bars: A, 1 m; B, 2.5 cm.
FIGURE 1. A in Description and taxonomic analysis of a tuberculated turtle leech from the Outer Banks, North Carolina, USA, provisionally identified as Placobdella multilineata Moore, 1953 (Hirudinea: Glossiphoniidae)
FIGURE 1. A, Map of the mid-Atlantic coastal plain showing location of the Albemarle region of the Outer Banks, North Carolina, USA. This wetlands (yellow shading) is the focus of an ongoing study of the Hirudinea. B, Close-up of locality stations (red stars) where over 675 Albemarle turtle leeches were collected in this study from 2008–2020. See Appendix for compilation of locality records. Scale bars: A, 100 km; B, 50 km. ABBREVIATIONS TO FIGURES. a, atrium; ae, accessory eye; ah, atrial horn; an, anus; b, 'brain'; cc, crop caecum; cl, 'colossal cells'; cu, detached cuticle; cup, detached cuticle of proboscis sheath; e, eye; ed, ejaculatory duct; f, female gonopore; g, ganglion; ic, intestinal caecum; lp, lateral head patch of segment IV; m, male gonopore; ma, metameric marginal pattern; mp, mouth pore; my, mycetome; oc, common ovisac; oe, oesophagus; op, posterior arm of ovisac; ov, vertical arm of ovisac; p, proboscis; pa, point of attachment; pb, base of proboscis; pd, paramedial stripe; pm, protractor muscle; pp, placobdellid head pattern; ps, proboscis sheath; pt, pre-anal tubercle; r, rectum; rm, retractor muscle; s, mid-dorsal stripe; sa, anterior salivary 'gland'; sb, common bundle of ductules from both salivary 'glands'; sd, bundle of ductules from salivary 'gland'; sp, posterior salivary 'gland'; pst, presumptive salivary tissue; sv, seminal vesicle; t2, second testisac; ta, paramarginal tubercle; ti, intermediate tubercle; tm, medial tubercle; tp, paramedial tubercle; ua, pre-ocular unpigmented area; vr, ventral rim of oral sucker; vs, ventral longitudinal stripe; wp, white patch.
FIGURE 15 in Description and taxonomic analysis of a tuberculated turtle leech from the Outer Banks, North Carolina, USA, provisionally identified as Placobdella multilineata Moore, 1953 (Hirudinea: Glossiphoniidae)
FIGURE 15. The multilinear pattern of dorsal tubercles in the Albemarle turtle leech correlates with the underlying crop caeca. For comparative purposes the intermediate tubercle (ti) of segment XIX is labelled in each respective image. A, orderly pattern of five rows of dorsal tubercles of an adult individual (PM-6). B, same individual as A under intense transmitted light showing the respective dorsal tubercles in relation to underlying blood-filled crop caeca. C, unfed embryo (4.8 mm) brooded by the adult in A, B, showing presumptive tubercles linked to the same respective crop caeca. A, reflected LED light. B, C, transmitted LED light. Scale bars: A, B, 5.0 mm; C, 0.2 mm.
Data from: Beyond thermal limits: comprehensive metrics of performance identify key axes of thermal adaptation in ants
How species respond to temperature change depends in large part on their physiology. Physiological traits, such as critical thermal limits (CTmax and CTmin), provide estimates of thermal performance but may not capture the full impacts of temperature on fitness. Rather, thermal performance likely depends on a combination of traits—including thermal limits—that vary among species. Here we examine how thermal limits correlate with the main components that influence fitness in ants. First, we compare how temperature affected colony survival and growth in two ant species that differ in their responses to warming in the field—Aphaenogaster rudis (heat-intolerant) and Temnothorax curvispinosus (heat-tolerant). We then extended our study to compare CTmax, thermal requirements of brood, and yearly activity season among a broader set of ant species. While thermal limits were higher for workers of T. curvispinosus than A. rudis, T. curvispinosus colonies also required higher temperatures for survival and colony growth. This pattern generalized across 17 ant species, such that species whose foragers had a high CTmax also required higher temperatures for brood development. Finally, species whose foragers had a high CTmax had relatively short activity seasons compared with less heat-tolerant species. The relationships between CTmax, thermal requirements of brood, and seasonal activity suggest two main strategies for growth and development in changing thermal environments: one where ants forage at higher temperatures over a short activity season, and another where ants forage at lower temperatures for an extended activity season. Where species fall on this spectrum may influence a broad range of life-history characteristics and aid in explaining the current distributions of ants as well as their responses to future climate change.
Data from: Markov-modulated continuous-time Markov chains to identify site- and branch-specific evolutionary variation in BEAST
<p>Markov models of character substitution on phylogenies form the foundation of phylogenetic inference frameworks. Early models made the simplifying assumption that the substitution process is homogeneous over time and across sites in the molecular sequence alignment. While standard practice adopts extensions that accommodate heterogeneity of substitution rates across sites, heterogeneity in the process over time in a site-specific manner remains frequently overlooked. This is problematic, as evolutionary processes that act at the molecular level are highly variable, subjecting different sites to different selective constraints over time, impacting their substitution behaviour. We propose incorporating time variability through Markov-modulated models (MMMs), which extend covarion-like models and allow the substitution process (including relative character exchange rates as well as the overall substitution rate) at individual sites to vary across lineages. We implement a general MMM framework in BEAST, a popular Bayesian phylogenetic inference software package, allowing researchers to compose a wide range of MMMs through flexible XML specification. Using examples from bacterial, viral and plastid genome evolution, we show that MMMs impact phylogenetic tree estimation and can substantially improve model fit compared to standard substitution models. Through simulations, we show that marginal likelihood estimation accurately identifies the generative model and does not systematically prefer the more parameter-rich MMMs. To mitigate the increased computational demands associated with MMMs, our implementation exploits recent developments in BEAGLE, a high-performance computational library for phylogenetic inference.</p>
Using 2D dental geometric morphometrics to identify modern Perognathus and Chaetodipus specimens (Rodentia, Heteromyidae)
<p></p><p>The Heteromyidae (pocket mice and kangaroo rats) are a group of extant small rodents abundant in western North America, as well as in fossil assemblages over the last 20 million years. Two genera of heteromyids, Chaetodipus and Perognathus, share similar tooth morphology and teeth are the primary fossil remains. Previous genetic studies show these extant sister genera likely diverged in the middle Miocene (~16 million years ago); however, the Chaetodipus fossil record starts in the Pleistocene (~2 million years ago). In this study, we asked whether two-dimensional geometric morphometrics on complete dentition and isolated premolars can accurately identify Chaetodipus and Perognathus specimens at the genus and species level. We landmarked the occlusal surface of the upper and lower tooth rows of modern Chaetodipus (n = 83) and Perognathus specimens (n = 80), including 12 of the 26 extant species across the two genera. We ran a canonical variates analysis to investigate whether principal component variation could predict known taxonomic identifications. The morphospace using complete dentition can identify specimens to genus with 90 – 92% accuracy and to species with more variable accuracy. We found an isolated premolar provides sufficient information for genus-level identification (69 – 84% accuracy), but not for species-level identification (26 – 56% accuracy). This morphospace of modern specimens can be used to identify the skeletal remains of Chaetodipus and Perognathus in museum collections, raptor pellets, or middens, to refine our existing knowledge of heteromyid evolutionary history.</p><p></p>
FIGURE 3. A–C, H, J in Primulina sinovietnamica (Gesneriaceae), a new species identified by both morphological and molecular characters from the limestone area in Guangxi, China
FIGURE 3. A–C, H, J) The ecotype of Primulina sinovietnamica in Longgang National Nature Reserve. A) overview of the landscape; B) habitat; C) habit; H) leaf surface; J) flower. D, I, K) The ecotype of P. sinovietnamica in Chunxiu Nature Reserve. D) habit; I) leaf surface; K) flower. E, L) P. pungentisepala. E) habit; L) flower. F, M) P. ningmingensis. F) habit; M) flower.
FIGURE 2. Primulina sinovietnamica. A in Primulina sinovietnamica (Gesneriaceae), a new species identified by both morphological and molecular characters from the limestone area in Guangxi, China
FIGURE 2. Primulina sinovietnamica. A) habit; B) leaf; C) opened corolla; D) stamens; E) pistil and opened calyx; F) stigma. Drawn by Yun-Xi Zhu.
FIGURE 8 in Synflorescence analysis in South American species of Andropogon section Leptopogon (Andropogoneae, Poaceae): a tool to identify different ploidy levels
FIGURE 8. Plot of scores by principal component axes 1 and 3 from 253 specimens of Andropogon sect. Leptopogon. Andropogon arenarius (), A. bicornis (), A. glaziovii (), A. hypogynus (), A. lateralis (), A. macrothrix (), A. leucostachyus (), A. selloanus () and A. ternatus (). PC1= 34.3 %, PC3= 10.9 %.
FIGURE 6 in Synflorescence analysis in South American species of Andropogon section Leptopogon (Andropogoneae, Poaceae): a tool to identify different ploidy levels
FIGURE 6. Diagrams of the enrichment zone in synflorescences of Andropogon sect. Leptopogon. A–B. Diploid species. A. A. macrothrix (Norrmann 115) and A. ternatus (Norrmann 74); B, A. leucostachyus (Norrmann 46) and A. selloanus (Norrmann 229). C–F. Hexaploid species. C. A. arenarius (Nagahama & Norrmann 29a); D. A. lateralis (Schinini et al. 16842); E. A. glaziovii (Norrmann 217a); F. A. bicornis (Norrmann & Quarín 91).
FIGURE 5 in Synflorescence analysis in South American species of Andropogon section Leptopogon (Andropogoneae, Poaceae): a tool to identify different ploidy levels
FIGURE 5. Variations of PcTTs in the section Leptopogon. A–B. Diploid species. A. Not ramified PcTT in A. macrothrix (Norrmann 115) and A. ternatus (Norrmann 74); B. PcTT showing a second ramification degree in A. leucostachyus (Norrmann 46) and A. selloanus (Norrmann 229); C–F. Hexaploid species. C. PcTT ramified from axillary buds of bracts and prophylls in A. arenarius (Nagahama & Norrmann 29a); D. PcTT ramified from axillary buds of bracts and prophylls in A. lateralis (Schinini et al. 16842); in this species the PcTT ramified from axillary buds of prophylls develops new PcTTs; E. PcTT showing numerous PcTTs developed from axillary buds of bracts and prophylls in A. glaziovii (Norrmann 217a); F. PcTT showing numerous PcTTs developed from axillary buds of bracts and prophylls in A. bicornis (Norrmann & Quarín 91).
FIGURE 7 in Synflorescence analysis in South American species of Andropogon section Leptopogon (Andropogoneae, Poaceae): a tool to identify different ploidy levels
FIGURE 7. Principal component analysis. Plot of scores by principal component axes 1 and 2 from 253 specimens of Andropogon sect. Leptopogon. Andropogon arenarius (), A. bicornis (), A. glaziovii (), A. hypogynus (), A. lateralis (), A. macrothrix (
FIGURE 2 in Synflorescence analysis in South American species of Andropogon section Leptopogon (Andropogoneae, Poaceae): a tool to identify different ploidy levels
FIGURE 2. Diagram of the synflorescence of Andropogon lateralis (Norrmann 71). Figure abbreviations: TT: trophotagma; UIF: unit of inflorescence; SIZ: short internodes zone; LIZ: long internodes zone; IZ: Innovation zone; HZ: Inhibition zone; EZ: Enrichment zone; b: bract; p: prophyll.
FIGURE 3 in Synflorescence analysis in South American species of Andropogon section Leptopogon (Andropogoneae, Poaceae): a tool to identify different ploidy levels
FIGURE 3. Andropogon bicornis (Norrmann & Quarín 91). A. synflorescence structure; B. basal axillary paracladium (PcTT1) (1 in A); C. cross-section (level 4 in E); D. distal zone of the synflorescence (3 in A); E. PcTT of middle zone of the synflorescence (2 in A). Figure abbreviations: TT: trophotagma; UIF: unit of inflorescence; SIZ: short internodes zone; LIZ: long internodes zone; IZ: Innovation zone; HZ: Inhibition zone; EZ: Enrichment zone; PcTT: paracladium of the trophotagma of first degree; PcTT´: paracladium of the trophotagma of second degree; PcTT´´: paracladium of the trophotagma of third degree; PcTT´´´: paracladium of the trophotagma of fourth degree; MA: main axis; pf: prophyll. Crosses represent units of inflorescence.
FIGURE 4 in Synflorescence analysis in South American species of Andropogon section Leptopogon (Andropogoneae, Poaceae): a tool to identify different ploidy levels
FIGURE 4. Diagram of the distal region of the EZ main axis and PcTTs in A. hypogynus (Krapovickas 12081). Figure abbreviations: EZ: enrichment zone; UIF: Unit of inflorescence; lPZ: long paracladia of the unit of inflorescences subzone; sPZ: short paracladia subzone; TsP: terminal short paracladium; st: sterile distal leaf (= spatheole); PcTT: paracladium of the trophotagma; b: bract; p: prophyll; filled ellipses: sessile spikelets; open ellipses: pedicellate spikelets.
FIGURE 1 in Synflorescence analysis in South American species of Andropogon section Leptopogon (Andropogoneae, Poaceae): a tool to identify different ploidy levels
FIGURE 1. Diagram of the synflorescence of Andropogon selloanus (Norrmann 73). Figure abbreviations: TT: trophotagma; UIF: unit of inflorescence; SIZ: short internodes zone; LIZ: long internodes zone; IZ: Innovation zone; HZ: Inhibition zone; EZ: Enrichment zone; PcTT1: first paracladium of the trophotagma; PcTT2: second paracladium of the trophotagma; PcTT2´: paracladium of the trophotagma of second degree in the PcTT2; b: bract; p: prophyll.
Data from: The challenges of recognising individuals with few distinguishing features: identifying red foxes Vulpes vulpes from camera-trap photos
Over the last two decades, camera traps have revolutionised the ability of biologists to undertake faunal surveys and estimate population densities, although identifying individuals of species with subtle markings remains challenging. We conducted a two-year camera-trapping study as part of a long-term study of urban foxes: our objectives were to determine whether red foxes could be identified individually from camera-trap photos, and highlight camera-trapping protocols and techniques to facilitate photo identification of species with few or subtle natural markings. We collected circa 800,000 camera-trap photos over 4945 camera days in suburban gardens in the city of Bristol, UK: 152,134 (19 %) included foxes, of which 13,888 (9 %) contained more than one fox. These provided 174,063 timestamped capture records of individual foxes; 170,923 were of foxes ≥ 3 months old. Younger foxes were excluded because they have few distinguishing features. We identified the individual (192 different foxes: 110 males, 49 females, 33 of unknown sex) in 168,417 (99 %) of these capture records; the remainder could not be identified due to poor image quality or because key identifying feature(s) were not visible. We show that carefully designed survey techniques facilitate individual identification of subtly-marked species. Accuracy is enhanced by camera-trapping techniques that yield large numbers of high resolution, colour images from multiple angles taken under varying environmental conditions. While identifying foxes manually was labour-intensive, currently available automated identification systems are unlikely to achieve the same levels of accuracy, especially since different features were used to identify each fox, the features were often inconspicuous, and their appearance varied with environmental conditions. We discuss how studies based on low numbers of photos, or which fail to identify the individual in a significant proportion of photos, risk losing important biological information, and may come to erroneous conclusions.
Identifying and classifying shared selective sweeps from multilocus data
Positive selection causes beneficial alleles to rise to high frequency, resulting in a selective sweep of the diversity surrounding the selected sites. Accordingly, the signature of a selective sweep in an ancestral population may still remain in its descendants. Identifying signatures of selection in the ancestor that are shared among its descendants is important to contextualize the timing of a sweep, but few methods exist for this purpose. We introduce the statistic SS-H12, which can identify genomic regions under shared positive selection across populations and is based on the theory of the expected haplotype homozygosity statistic H12, which detects recent hard and soft sweeps from the presence of high-frequency haplotypes. SS-H12 is distinct from comparable statistics because it requires a minimum of only two populations, and properly identifies and differentiates between independent convergent sweeps and true ancestral sweeps, with high power and robustness to a variety of demographic models. Furthermore, we can apply SS-H12 in conjunction with the ratio of statistics we term H2Tot and H1Tot to further classify identified shared sweeps as hard or soft. Finally, we identified both previously-reported and novel shared sweep candidates from human whole-genome sequences. Previously-reported candidates include the well-characterized ancestral sweeps at LCT and SLC24A5 in Indo-Europeans, as well as GPHN worldwide. Novel candidates include an ancestral sweep at RGS18 in sub-Saharan Africans involved in regulating the platelet response and implicated in sudden cardiac death, and a convergent sweep at C2CD5 between European and East Asian populations that may explain their different insulin responses.
Data from: Candidate adaptive genes associated with lineage divergence: identifying SNPs via next-generation targeted resequencing in mule deer (Odocoileus hemionus)
Mule deer (Odocoileus hemionus) are an excellent nonmodel species for empirically testing hypotheses in landscape and population genomics due to their large population sizes (low genetic drift), relatively continuous distribution, diversity of occupied habitats and phenotypic variation. Because few genomic resources are currently available for this species, we used exon data from a cattle (Bos taurus) reference genome to direct targeted resequencing of 5935 genes in mule deer. We sequenced approximately 3.75 Mbp at minimum 20X coverage in each of the seven mule deer, identifying 23 204 single nucleotide polymorphisms (SNPs) within, or adjacent to, 6886 exons in 3559 genes. We found 91 SNP loci (from 69 genes) with putatively fixed allele frequency differences between the two major lineages of mule deer (mule deer and black-tailed deer), and our estimate of mean genetic divergence (genome-wide FST = 0.123) between these lineages was consistent with previous findings using microsatellite loci. We detected an over-representation of gamete generation and amino acid transport genes among the genes with SNPs exhibiting potentially fixed allele frequency differences between lineages. This targeted resequencing approach using exon capture techniques has identified a suite of loci that can be used in future research to investigate the genomic basis of adaptation and differentiation between black-tailed deer and mule deer. This study also highlights techniques (and an exon capture array) that will facilitate population genomic research in other cervids and nonmodel organisms.
Supplementary material 3 from: Hardisty AR, Addink W, Glöckler F, Güntsch A, Islam S, Weiland C (2021) A choice of persistent identifier schemes for the Distributed System of Scientific Collections (DiSSCo). Research Ideas and Outcomes 7: e67379. https://doi.org/10.3897/rio.7.e67379
Comparison of main roles and responsibilities in the two main categories of administration of a Handle-based PID scheme
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.