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
datasets available to search
ShareScore release 0.9.0
Dataset results
11 results for “Haematobosca”
Fig. 10 in Wing geometric morphometrics to distinguish and identify Haematobosca flies (Diptera: Muscidae) from Thailand
Fig. 10. Hierarchical agglomerative clustering tree based on shape similarities of test specimens (male as yellow and female as gray) and reference data of Haematobosca sanguinolenta and H. aberrans. Euclidean distances were used for the construction of the tree. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Wing geometric morphometrics to distinguish and identify Haematobosca flies (Diptera: Muscidae) from Thailand
Fig. 2. The topographic map of the Haematobosca fly collection sites in Thailand: Chiang Mai (1), Kanchanaburi (2), and Nakhon Ratchasima (3) (A). The Nzi trap used for fly collection was placed near animal hosts at each collection site (B, C). This map was prepared from the United States Geological Survey (USGS) National Map Viewer available at http://viewer.nationalmap.gov/viewer/, accessed on February 10, 2023.
Fig. 9 in Wing geometric morphometrics to distinguish and identify Haematobosca flies (Diptera: Muscidae) from Thailand
Fig. 9. Factor map of the principal components (PC1, 46% as horizontal axis and PC2, 22% as vertical axis) from wing shape variables of test specimens (male and female) and reference data of Haematobosca sanguinolenta and H. aberrans. Squares represent mean values in each group.
Fig. 8 in Wing geometric morphometrics to distinguish and identify Haematobosca flies (Diptera: Muscidae) from Thailand
Fig. 8. Linear regression between centroid size and the first shape-based principal component (PC) of Haematobosca sanguinolenta (A) and H. aberrans (B). Linear regression prediction is shown by the orange dots. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3. The 10 in Wing geometric morphometrics to distinguish and identify Haematobosca flies (Diptera: Muscidae) from Thailand
Fig. 3. The 10 landmarks on the wing of Haematobosca flies used in the wing geometric morphometric analysis.
Fig. 7 in Wing geometric morphometrics to distinguish and identify Haematobosca flies (Diptera: Muscidae) from Thailand
Fig. 7. Hierarchical agglomerative clustering tree based on shape similarities of each individual for male and female Haematobosca sanguinolenta and H. aberrans. Euclidean distances were used for the construction of the tree.
Fig. 1 in Wing geometric morphometrics to distinguish and identify Haematobosca flies (Diptera: Muscidae) from Thailand
Fig. 1. Heads in the lateral view and the pleura of Haematobosca sanguinolenta (A, B) and H. aberrans (C, D). The anterior and posterior katepisternal setae (arrow) were used to distinguish between both species. Photographs were prepared by the authors.
Fig. 5 in Wing geometric morphometrics to distinguish and identify Haematobosca flies (Diptera: Muscidae) from Thailand
Fig. 5. Mean shape of male (A) and female (B) Haematobosca sanguinolenta and H. aberrans after Procrustes superimposition.
Fig. 6 in Wing geometric morphometrics to distinguish and identify Haematobosca flies (Diptera: Muscidae) from Thailand
Fig. 6. Factor map of the first two principal components (PC1, 47% as horizontal axis and PC2, 33% as vertical axis) of wing shape variables (A) and factor map of the first two discriminant factors (DF1, 66.8% as horizontal axis and DF2, 31.8% as vertical axis, the two discriminant factors represent 98.6% of the total discriminant space) of wing shape variables (B). Each point represents the individuals of male and female Haematobosca sanguinolenta and H. aberrans, and each polygon corresponds to a different species and sex. Squares represent the mean values in each group.
FIGURES 5–7 in A new species of Haematobosca Bezzi (Diptera: Muscidae) from Thailand
FIGURES 5–7. Haematobosca aberrans sp. nov. 5, Male pleura (holotype). 6, Male right wing (holotype). 7, Male abdomen, viewed from above and behind (holotype).
FIGURES 1–4 in A new species of Haematobosca Bezzi (Diptera: Muscidae) from Thailand
FIGURES 1–4. Haematobosca aberrans sp. nov. 1, Male head, in frontal view (holotype). 2, Male head, in lateral view (holotype). 3, Female frons, in dorsal view (paratype). 4, Male scutum, viewed from above and behind (holotype).
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.