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.
22
datasets available to search
ShareScore release 0.9.0
Dataset results
22 results for “hairworm”
Figure 6 from: Swanteson-Franz RJ, Marquez DA, Goldstein CI, Schmidt-Rhaesa A, Bolek MG, Hanelt B (2018) New hairworm (Nematomorpha, Gordiida) species described from the Arizona Madrean Sky Islands. ZooKeys 733: 131-145. https://doi.org/10.3897/zookeys.733.22798
Figure 6 . Relationships inferred by maximum likelihood. Tree is unrooted, and drawn to scale indicating number of substitutions per site. Bootstrap values above 0.90 are shown.
Supplementary materials for "The importance of biological variables in SDMs of species with strict interactions: a case study with a hairworm and its hosts"
<p>Species distribution model (SDM) has conventionally been based mainly on abiotic factors, i.e., temperature and precipitation variables. Although recent studies have shown that incorporating biotic factors may improve the model performance, only few empirical studies could effectively incorporate biotic factors in SDMs. Here we used a parasite and host system to investigate whether incorporating biotic information can improve SDM. Specifically, SDM of the parasite based on hosts’ distributions can be helpful because the distribution of the parasite may depend on the dispersal ability of the hosts. We evaluated the most important layer, including the SDMs of its three hosts, for predicting the distribution of the parasitic horsehair worm <em>Chordodes formosanus</em>.<br> We retrieved presence points for three host species and the parasite. We first built the three hosts’ SDMs. We subsequently built SDMs for the parasite with MaxEnt implemented in ENMeval by using bioclim variables (chosen according to VIF values) and the aforementioned host SDMs built at 30 seconds scale. In addition, we evaluated niche overlap among hosts and parasite according to five similarity indices (Schoener’s D, I statistic, relative rank, Pearson correlation coefficient and the rank correlation coefficient rho).<br> According to percentage and permutation importance, the presence of the Taiwanese giant mantis, <em>Titanodula formosana</em>, was the main variable that explained the distribution of <em>C. formosanus</em>. In addition, habitat suitability models showed high similarity between hosts and the parasite, according to niche overlap estimations.<br> Accounting for biological interaction is critical for SDM as shown here that the distribution of the main final host effectively predicts the distribution of the parasite. Additionally, SDMs can be helpful to prioritize host sampling and by consequence parasite sampling, too. SDMs are reliable tools for host and parasite conservation management and it is hoped their use will help to improve biological and ecological knowledge of parasites.</p>
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.