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.
10
datasets available to search
ShareScore release 0.9.0
Dataset results
10 results for “amplified fragment length polymorphism”
Figure 3 in Amplified fragment length polymorphisms, the evolution of the land snail genus Theba (Stylommatophora: Helicidae), and an objective approach for relating fossils to internal nodes of a phylogenetic tree using geometric morphometrics
Figure 3. Thin plate splines illustrating shape changes between selected nodes of the tree in Figure 4 based on weighted branch lengths.
Figure 4 in Amplified fragment length polymorphisms, the evolution of the land snail genus Theba (Stylommatophora: Helicidae), and an objective approach for relating fossils to internal nodes of a phylogenetic tree using geometric morphometrics
Figure 4. Reconstruction of shell shape and size based on weighted (above branches) and unweighted (below branches) branch lengths. The inset shows the tree shape based on COI sequence data evolved into the AFLP tree topology. Node numbers are in italic; size is expressed as centroid size; the colour of the centroid size values indicates shape changes.
Figure 6 in Species boundaries in Philaethria butterflies: an integrative taxonomic analysis based on genitalia ultrastructure, wing geometric morphometrics, DNA sequences, and amplified fragment length polymorphisms
Figure 6. Evolutionary relationships of Philaethria based on DNA sequences from specimens of Philaethria wernickei (southern population; Atlantic Rain Forest) and individuals previously described as Philaethria pygmalion (northern population; Amazon Forest), depicted by the green shading (grey in print version). Philaethria diatonica and Philaethria dido were used to root the tree. Purple (grey) circles represent individuals from the Atlantic Rain Forest and black triangles indicate samples from the Amazon Basin. A, consensus Bayesian tree based on mitochondrial (cytochrome oxidase subunit I, Co-I) and nuclear [triose-phosphate isomerase (Tpi), wingless (Wg), and tyrosine hydroxylase (TH)] DNA sequences. Posterior probabilities are shown above branches. Bootstrap node support based on maximum likelihood analysis is indicated below branches. Asterisks indicate node support lower than 70%. B, Median-joining network based on mtDNA and nuclear loci sequence data describing the relationship between haplotypes (purple indicates southern population, and black, northern population). Nucleotide substitutions are shown on the branches as small transverse bars. Circle size is proportional to haplotype frequency.
Figure 2 in Species boundaries in Philaethria butterflies: an integrative taxonomic analysis based on genitalia ultrastructure, wing geometric morphometrics, DNA sequences, and amplified fragment length polymorphisms
Figure 2. Location of linear measurements (A) and schematic representation (B, C) of Philaethria wings showing veins and landmarks adopted in this study. A, hind wing dorsal and ventral (detail) views, showing measured vectors. B, fore wing. C, hind wing. See Appendix S2 for details on morphological definitions of landmarks.
Figure 4 in Species boundaries in Philaethria butterflies: an integrative taxonomic analysis based on genitalia ultrastructure, wing geometric morphometrics, DNA sequences, and amplified fragment length polymorphisms
Figure 4. Linear variation in hind wing size and medial postdiscal bands for Philaethria wernickei and Philaethria pygmalion (left column), and in relation to latitude when samples from the two species are combined (right column). A, D, hind wing length. B, E, hind wing length/postdiscal band ratio (AB/DE). C, F, inner and medial postdiscal band ratio (EF/DF). See Fig. 2A for details on wing position of corresponding measurements. Numbers above boxes indicate the number of specimens measured in each class.
Figure 1 in Species boundaries in Philaethria butterflies: an integrative taxonomic analysis based on genitalia ultrastructure, wing geometric morphometrics, DNA sequences, and amplified fragment length polymorphisms
Figure 1. Geographical distributions of Philaethria wernickei and Philaethria pygmalion, and corresponding variation in male genitalia ultrastructure and ventral hind wing colour. A, shaded areas show distribution ranges proposed by Constantino & Salazar (2010) for P. wernickei (green) and P. pygmalion (red); green circles and red triangles represent collection localities of the material analysed in this study. B, variation in valva's cucullus, external view. C, variation in the colour pattern of hind wing surface, ventral view.
Figure 3 in Species boundaries in Philaethria butterflies: an integrative taxonomic analysis based on genitalia ultrastructure, wing geometric morphometrics, DNA sequences, and amplified fragment length polymorphisms
Figure 3. Male genitalia of Philaethria wernickei and Philaethria pygmalion. A, P. wernickei, lateral view. B, P. pygmalion, lateral view. C, schematic representation of generalized genitalia for both, in lateral view. D, F, H, J, scanning electron micrographs of P. wernickei; E, G, I, K, scanning electron micrographs of P. pygmalion. D, E, ampulla external view. F, G, ampulla internal view. H, I, ampulla ornamentation in detail. J, K, fultura inferior distal end. Scale bars = 150, 30, and 100 μm, for D–G, H–I, and J–K, respectively.
Figure 8 in Species boundaries in Philaethria butterflies: an integrative taxonomic analysis based on genitalia ultrastructure, wing geometric morphometrics, DNA sequences, and amplified fragment length polymorphisms
Figure 8. STRUCTURE-based clustering of Philaethria wernickei individuals from low (0–10°S) to high (20–25°S) latitudes (north and south populations, respectively) based on amplified fragment length polymorphism loci. Each individual is represented by a vertical line divided into segments of different colour that represent genetic clusters (K) from 1–4.
Figure 7 in Species boundaries in Philaethria butterflies: an integrative taxonomic analysis based on genitalia ultrastructure, wing geometric morphometrics, DNA sequences, and amplified fragment length polymorphisms
Figure 7. Multilocus consensus Bayesian tree based on cytochrome oxidase subunit I (Co-I), triose-phosphate isomerase (Tpi), wingless (Wg), and tyrosine hydroxylase (TH) sequences from specimens of Philaethria wernickei (Atlantic Rain Forest, purple circles) and individuals previously described as Philaethria pygmalion (Amazon Forest, black triangles) depicted by the green shading (grey in print version). Philaethria pygmalion and Philaethria dido were used to root the tree. Posterior probabilities are shown above branches and bootstrap node support based on maximum likelihood analysis is indicated below branches. Asterisks indicate node support lower than 70%.
Data from: Microsatellites for the marsh Fritillary butterfly: de novo transcriptome sequencing, and a comparison with amplified fragment length polymorphism (AFLP) markers
Open the record for dataset details and reuse information.
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.