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.
10,950
datasets available to search
ShareScore release 0.9.0
Dataset results
10,950 results for “hosting”
Simple attributes predict the value of plants as hosts to fungal and arthropod communities
Fungal and arthropod consumers constitute the vast majority of global terrestrial biodiversity. Yet, the link from richness and composition of producer (plant) communities to the richness of consumer communities is poorly understood. Fungal and arthropod species richness could be a simple function of producer species richness at a site. Alternatively, it could be a complex function of chemical and structural properties of the producer species making up communities. We used databases on plant-fungus and plant-arthropod trophic links to derive the richness of consumer biota per associated plant species (coined link score). We assessed how well link scores could be predicted by simple attributes of plant species. Next, we used a multi-taxon inventory of 130 sites, representing all major habitat types in a country (Denmark), to investigate whether link scores summed over plant species in communities (coined link sum) could outperform simple plant species richness as predictor of fungal and arthropod richness at the sites. We found plant species' link scores for both fungi and arthropods to be positively related to plant size, regional occupancy, nativeness and ectomycorrhizal status. Link-based indices generally improved the prediction of richness of fungal and arthropod communities. For fungal communities, both observed link sum (from databases) and predicted link sum (from plant attributes) had high predictive power, while plant richness alone had none. For arthropod communities, predictive performance varied between functional groups. For both fungi and arthropods, richness predictions were further improved by considering abiotic habitat conditions. Our results underline the importance of plants as niche space for the megadiverse groups of arthropods and fungi. The plant-attribute approach holds promise for predicting local and regional consumer richness in areas of the world lacking detailed plant-consumer databases.
Imprints of latitude, host taxon and decay stage on fungus-associated arthropod communities
<p>Interactions among fungi and insects involve hundreds of thousands of species. While insect communities on plants have formed some of the classic model systems in ecology, fungus-based communities and the forces structuring them remain poorly studied by comparison. We characterize the arthropod communities associated with fruiting bodies of eight mycorrhizal basidiomycete fungus species from three different orders along a 1200-km latitudinal gradient in northern Europe. We hypothesized that—matching the pattern seen for most insect taxa on plants—we would observe a general decrease of fungal-associated species with latitude. Against this backdrop, we expected local communities to be structured by host identity and phylogeny, with more closely related fungal species sharing more similar communities of associated organisms. As a more unique dimension added by the ephemeral nature of fungal fruiting bodies, we expected further imprints generated by successional change, with younger fruiting bodies harboring communities different from older ones. Using DNA metabarcoding to identify arthropod communities from fungal fruiting bodies, we find that latitude leaves a clear imprint on fungus-associated arthropod community composition, with host phylogeny and decay stage of fruiting bodies leaving lesser but still-detectable effects. The main latitudinal imprint is on a high arthropod species turnover, with no detectable pattern in overall species richness. Overall, these findings paint a new picture of the drivers of fungus-associated arthropod communities, suggesting that latitude will not affect <i>how many</i> arthropod species inhabits a fruiting body, but rather <i>what</i> species occur in it and <i>at w</i>hat relative abundances (as measured by sequence read counts). These patterns upset simplistic predictions regarding latitudinal gradients in species richness and in the strength of biotic interactions.</p>
Host-symbiont stress response to lack-of-sulfide in the giant ciliate mutualism
<p>The mutualism between the thioautotrophic bacterial ectosymbiont <em>Candidatus</em> Thiobius zoothamnicola and the giant ciliate <em>Zoothamnium niveum</em> thrives in a variety of shallow-water marine environments with highly fluctuating sulfide emissions. To persist over time, both partners must reproduce and ensure the transmission of symbionts before the sulfide stops, which enables carbon fixation of the symbiont and nourishment of the host. We experimentally investigated the response of this mutualism to depletion of sulfide. We found that colonies released some initially present but also newly produced macrozooids until death, but in fewer numbers than when exposed to sulfide. The symbionts on the colonies proliferated less without sulfide, and became larger and more rod-shaped than symbionts from freshly collected colonies that were exposed to sulfide and oxygen. The symbiotic monolayer was severely disturbed by growth of other microbes and loss of symbionts. We conclude that the response of both partners to the termination of sulfide emission was remarkably quick. The development and the release of swarmers continued until host died and thus this behavior contributed to the continuation of the association.</p>
Data analysis pipeline for investigating drug-host-microbiome relationships in cardiometabolic disease (MetaCardis cohort).
<p>*******************************************************************<br> MetaDrugs workflow<br> *******************************************************************</p> <p>Data analysis pipeline for investigating drug-host-microbiome relationships in cardiometabolic disease (MetaCardis cohort).</p> <p>For questions and requests, please contact:<br> Sofia K. Forslund (sofia.forslund@mdc-berlin.de)<br> and Till Birkner (till.birkner@mdc-berlin.de)</p> <p>*******************************************************************<br> Contents:<br> -------------------------------------------------------------------<br> Data files:<br> metadata.tar.gz - archived cohort metadata files*<br> input_features.tar.gz - archived preprocessed serum and urine metabolome and gut microbiome features<br> output_complete.tar.gz - archived example analysis output files for each of the input feature file<br> output_rerun.tar.gz - archived empty directory for generating test output files as described in this document<br> <br> *Please note: Due to conflicts with Danish Data Protection laws, metadata from the Danish subset of the cohort were removed in this repository. Please reach out for a potential case-by-case access request for access to the complete set of metadata.<br> -------------------------------------------------------------------<br> Text files:<br> archived in feature_names.tar.gz:<br> atcs_names - full names for atcs drug compounds<br> contrast_names - full names for disease comparison groups<br> file_names - brief description of the files in input_features folder<br> gmm_names - full names of GMM modules<br> kegg_names - full names of KEGG modules<br> ko_names - full names of KO modules<br> metadata_names - full names of metadata features<br> mOTU_names - species names for metagenomics data<br> taxon_names - taxon names for metagenomics data<br> -------------------------------------------------------------------<br> Scripts:<br> -------------------------------------------------------------------<br> runFrame.r - main wrapper script envoking the analysis pipeline<br> -------------------------------------------------------------------<br> runFrame_rel_comb.r - script calculating drug combination effects<br> runFrame_rel.r - script calculating dosage effects<br> testCombPresenceSeparate.r - testing of significant drug combination effects beyond single drug effects<br> testDosagePresenceSeparate.pl - testing of significant drug dosage effects beyond single drug effects<br> testDosagePresenceSeparateNegative.pl - testing of unique drug dosage effects beyond single drug effects<br> -------------------------------------------------------------------<br> prettifyResults_uncollapsed.pl - wrapper scripts to create and format a single analysis output file<br> makeTables.r - wrapper script to make excel tables with analysis results<br> -------------------------------------------------------------------<br> Example output file:<br> -------------------------------------------------------------------<br> output_all_formatted_noc_uncollapsed_complete.tsv - contains all disease-drug-host-microbiome feature analysis results in one place.<br> *******************************************************************</p>
Kinematic catalog of 2,174 planet host stars from Planet across space and time (PAST). I
<p>We present a catalog of kinematic properties (i.e., Galactic positions, velocities, and the relative membership probabilities among the thin disk, thick disk, Hercules stream, and the halo) as well as other basic stellar parameters (e.g., effective temperature, metallicity) for 2174 host stars of 2872 planets by combining data from Gaia DR2, LAMOST DR4, APOGEE DR16, RAVE DR5, and the NASA exoplanet archive by applying the revised kinematic methods from Planet across space and time (PAST). I.</p> <p>we will continue to update our catalogue with the release of new data in the future.</p> <p> </p>
Photographs of parasites encapsulated in Cepaea nemoralis shells (appendix to the paper "Morph-dependent effect of nematode infection on host movement in the land snail *Cepaea nemoralis* (Mollusca, Gastropoda)")
<p>A set of four photographs taken of shell fragments of Cepaea nemoralis (grove snail), taken in the course of the project leading to the manuscript titled: "Morph-dependent effect of nematode infection on host movement in the land snail *Cepaea nemoralis* (Mollusca, Gastropoda)". Each photograph shows a parasite encapsulated/trapped in the shell by the snail:</p> <p>AcaRX3_3.tif: a mite (presumably Riccardoella sp.)<br> NemaBX7_1.tif, NemaBX7_3.tif, NemaRK5_2.tif: unidentified nematodes (note in the latter image, the clearly visible brown-band on yellow background pattern of the shell).</p> <p>A scale bar (0.25 mm) is overlaid on each image</p> <p> </p>
Environmental drivers of biseasonal anthrax outbreak dynamics in two multi-host savanna systems
<p>Environmental factors are common forces driving infectious disease dynamics. We compared inter-annual and seasonal patterns of anthrax infections in two multi-host systems in southern Africa: Etosha National Park, Namibia, and Kruger National Park, South Africa. Using several decades of mortality data from each system, we assessed possible transmission mechanisms behind anthrax dynamics, examining 1) within- and between-species case correlations, and 2) associations between anthrax mortalities and environmental factors, specifically rainfall and the Normalized Difference Vegetation Index (NDVI). Anthrax cases in Kruger had wide inter-annual variation in case numbers, and large outbreaks seemed to follow roughly a decadal cycle. In contrast, outbreaks in Etosha were smaller in magnitude and occurred annually. In Etosha, the host species commonly affected remained consistent over several decades, although plains zebra (<em>Equus quagga</em>) became relatively more dominant. In Kruger, turnover of the main host species occurred after the 1990s, where the previously dominant host species, greater kudu (<em>Tragelaphus strepsiceros</em>), was replaced by impala (<em>Aepyceros melampus</em>). In both parks, anthrax infections showed two seasonal peaks, with each species having only one peak in a year. Zebra, springbok (<em>Antidorcas marsupialis</em>), wildebeest (<em>Connochaetes taurinus</em>) and impala cases peaked in wet seasons, while elephant (<em>Loxodonta africana</em>), kudu and buffalo (<em>Syncerus caffer</em>) cases peaked in dry seasons. For common host species shared between the two parks, anthrax mortalities peaked in the same season in both systems. Among host species with cases peaking in the same season, anthrax mortalities were mostly synchronized, which may imply similar transmission mechanisms or shared sources of exposure. Between seasons, outbreaks in one species may contribute to more cases in another species in the following season. Higher vegetation greenness was associated with more zebra and springbok anthrax mortalities in Etosha, but fewer elephant cases in Kruger. These results suggest that host behavioral responses to changing environmental conditions may affect anthrax transmission risk, with differences in transmission mechanisms leading to multi-host biseasonal outbreaks. This study reveals the dynamics and potential environmental drivers of anthrax in two savanna systems, providing a better understanding of factors driving biseasonal dynamics and outbreak variation among locations.</p>
Comparative host transcriptomics as a tool to identify candidate biomarkers for immune reactions in leprosy: A meta-analysis study
<p>The dataset consists of R source code for the individual dataset analysis of the studies and their meta-analysis. It also contains supplementary tables and figure.</p>
Ammophila Host (Poaceae) in Flora iberica XIX(II)
<p>Testimonios de herbario en los que se basan los resultados del capítulo correspondiente al género <em>Ammophila</em> Host (Poaceae), publicado en el libro <em>Flora iberica</em>, vol. XIX(II) Gramineae (partim), ISBN: 978-84-00-10817-5, páginas: 972-975 (2021).</p>
Data for Corre et al., Bacterial matrix metalloproteases and serine proteases contribute to the extra-host inactivation of enterovirus in lake water, ISMEJ 2022
<p>Data for Corre et al., <em>Bacterial matrix metalloproteases and serine proteases contribute to the extra-host inactivation of enterovirus in lake water</em>, ISMEJ 2022</p> <p>The first file contains all data pertaining to experiments with isolates: collection date, isolation temperature, protease activity measured by 4 different approaches, antiviral effect on E11 and CVA9 (three replicates each); this table corresponds to the data shown in Supplementary Table 2.</p> <p>The second file contains the raw data for all lake water experiments (Figures 1 and 6): information on sample type, antiviral effect (measured in triplicate), presence of a protease inhibitor.</p>
Host and pathogen gene expression profiles in Necrotizing Soft Tissue Infections
<p>Data underlying the article</p> <p><strong>Analysis of host-pathogen gene association networks reveals patient-specific response to streptococcal and poly-microbial necrotizing soft tissue infections</strong></p> <p>Sanjeevan Jahagirdar<sup>1</sup>, Lorna Morris<sup>2</sup>, Nirupama Benis<sup>3</sup>, Oddvar Oppegaard<sup>4</sup>, Mattias Svenson<sup>5</sup>,<sup> </sup>Ole Hyldegaard<sup>6</sup>, Steinar Skrede<sup>4,7</sup>, Anna Norrby-Teglund<sup>5</sup>, INFECT Study group, Vitor A. P. Martins dos Santos<sup>1,2</sup>, Edoardo Saccenti<sup>1*</sup></p> <p><sup>Contains</sup></p> <p>Data described in 4.3.2 Sample Selection and in Figure 6:</p> <p>INFECT_DualRNASeq_norm_counts_Human.txt Normalised counts from Kallisto mapping to GRCh38 (release 91) for 81 NSTI patients</p> <p>INFECT_DualRNASeq_relative_abundance_Bacteria.txt Relative abundance for all species from HumanN2 mapping for 81 NSTI patients</p> <p>BStrep_filtered_D1 - INFECT_DualRNASeq_relative_abundance_Bacteria.txt filtered for samples classified as Streptococcal from Thänert <em>et al </em>(2019) taken on the day of admission (day 1).</p> <p>BPoly_filtered_D1 - INFECT_DualRNASeq_relative_abundance_Bacteria.txt filtered for samples classified as polymicrobial from Thänert <em>et al </em>(2019) taken on the day of admission (day 1).</p> <p>HStrep_filtered_D1 - INFECT_DualRNASeq_norm_counts_Human.txt filtered for samples classified as Streptococcal from Thänert <em>et al </em>(2019) taken on the day of admission (day 1).</p> <p>HPoly_filtered_D1 - INFECT_DualRNASeq_norm_counts_Human.txt filtered for samples classified as polymicrobial from Thänert <em>et al </em>(2019) taken on the day of admission (day 1).</p>
Fig. 4 in Redescription And New Host Record Of Diplostamenides Sciaenae (Monogenea, Microcotylidae) And Its Phylogenetic Status Using Molecular Markers
Fig. 4. Phylogenetic tree topology of partial 18S rRNA nucleotide sequence data for different microcotylids and outgroup as diclidophorids through NJ and ME methods. The bootstrap values for 1000 replicates are shown as in the phylogram and branch length is genetic distance between taxa.
Fig. 3 in Redescription And New Host Record Of Diplostamenides Sciaenae (Monogenea, Microcotylidae) And Its Phylogenetic Status Using Molecular Markers
Fig. 3. Phylogenetic tree topology of parital 28S rRNA nucleotide sequence data for the members of microcotytlidae and outgroup of members of diclidophoridae through NJ and ME methods. The bootstrap values for 1000 replicates are shown as in the phylogram and branch length is genetic distance between taxa.
Fig. 1 in Redescription And New Host Record Of Diplostamenides Sciaenae (Monogenea, Microcotylidae) And Its Phylogenetic Status Using Molecular Markers
Fig. 1. Diplostamenides sciaenae: A — whole mount (ventral view): OS, oral sucker; P, pharyn×; OE, oesophagus; GA, genital atrium; IC, intestinal caecum; VI, vitellarium; H, haptor; C, clamp B — reproductive system: V, vas deferens; VD, vitelline duct; O, ovary; CVD, common vitelline duct; GIC, genitointestinal canal; OD, oviduct; OT, ootype; T, testes C — genital atrium and spines: AS, atrial spines; D — clamp and associated sclerites: SMD, scleritum marginal dorsale; SMV, scleritum marginal ventrale; SM, Scleritum median; SOB, scleritum obliqum basale; ETD, extreme terminal dorsale; ETV, extreme terminal ventrale.
Fig. 2 in Redescription And New Host Record Of Diplostamenides Sciaenae (Monogenea, Microcotylidae) And Its Phylogenetic Status Using Molecular Markers
Fig. 2. Diplostamenides sciaenae digital phototmicrographs (present study): A — whole mount; B — clamp and associated sclerites; C — gential atrium and spines; D — anterior region with oral suckers, pharyn× and oesophagus. Abbreviations are provided in figure 1.
Fig. 1– 6 in Distribution And Host Record Of Bruchophagus Robiniae (Hymenoptera, Eurytomidae) In Turkey
Fig. 1– 6. Bruchophagus robiniae Zerova: 1, 3–5 — female; 2, 6 — male; 1, 2 — lateral view; 3 — head, 4 — marginal and radial veins, 5, 6 — antenna.
Fig. 4 in The Role Of Different Mollusk Species In Maintaining The Transmission Of Polyhostal Trematode Species In Ukrainian Polissya Waters: The Specificity Of Trematode Parthenogenetic Generations To Mollusk Hosts
Fig. 4. The distribution of olygoxenic three-host trematode species in the parthenitae host species of mollusks: A — E. stantschinskii; B — P. ovata; C — C. cornutus; D — T. clavata.
Fig. 3 in The Role Of Different Mollusk Species In Maintaining The Transmission Of Polyhostal Trematode Species In Ukrainian Polissya Waters: The Specificity Of Trematode Parthenogenetic Generations To Mollusk Hosts
Fig. 3. The distribution of polyxenic trematode species in the parthenitae host species of mollusks: A — H. conoideum; B — E. recurvatum.
Fig. 6 in The Role Of Different Mollusk Species In Maintaining The Transmission Of Polyhostal Trematode Species In Ukrainian Polissya Waters: The Specificity Of Trematode Parthenogenetic Generations To Mollusk Hosts
Fig. 6. The distribution of olygoxenic two-host trematode species in the parthenitae host species of mollusks: A — P. ichikawai; B — D. subclavatus; C — F. hepatica; D — L. constantinovae; E — A. imitans.
Fig. 2 in The Role Of Different Mollusk Species In Maintaining The Transmission Of Polyhostal Trematode Species In Ukrainian Polissya Waters: The Specificity Of Trematode Parthenogenetic Generations To Mollusk Hosts
Fig. 2. The distribution of olygoxenic three-host trematode species in the parthenitae host species of mollusks: A — H. cylindracea; B — H. variegatus; C — E. aconiatum; D — E. revolutum.
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.