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Dataset results
19 results for “higher-order interaction”
Data from: Direct and higher-order interactions in plant communities under increasing weather persistence
<p>ABSTRACT: Climate change is increasing the weather persistence in the midlatitudes, prolonging both dry and wet spells compared to historic averages. These newly emerging environmental conditions destabilize plant communities, but the role of species interactions in this process is unknown. Here, we tested how direct and higher-order interactions (HOIs) between species may change in synthesized grassland communities along an experimental gradient of increasing persistence in precipitation regimes. Our results indicate that species interactions (including HOIs) are an important determinant of plant performance under increasing weather persistence. Out of the 12 most parsimonious models predicting species productivity, 75 % contained significant direct interactions and 92 % significant HOIs. Inclusion of direct interactions or HOIs respectively tripled or quadrupled the explained variance of target species biomass compared to null models only including the precipitation treatment. Drought dominated the plant responses, with longer droughts increasing direct competition but also HOI-driven facilitation. Despite these counteracting changes, drought intensified net competition. Grasses were generally more involved in competitive interactions whereas legumes had a stronger affinity for facilitative interactions. Under longer drought, species affinity for nutrient rich or wet environments resulted in more negative direct interactions or HOIs, respectively. We conclude that higher-order interactions, crucially depending on species identity, only partially stabilize community dynamics under increasing weather persistence</p>
Data from: Direct and higher-order interactions in plant communities under increasing weather persistence
<p>Climate change is increasing the weather persistence in the mid-latitudes, prolonging both dry and wet spells compared to historic averages. These newly emerging environmental conditions destabilize plant communities, but the role of species interactions in this process is unknown. Here, we tested how direct and higher-order interactions (HOIs) between species may change in synthesized grassland communities along an experimental gradient of increasing persistence in precipitation regimes. Our results indicate that species interactions (including HOIs) are an important determinant of plant performance under increasing weather persistence. Out of the 12 most parsimonious models predicting species productivity, 75 % contained significant direct interactions and 92 % significant HOIs. Inclusion of direct interactions or HOIs respectively tripled or quadrupled the explained variance of target species biomass compared to null models only including the precipitation treatment. Drought was the main driver of plant responses, with longer droughts increasing direct competition but also HOI-driven facilitation. Despite these counteracting changes, drought intensified net competition. Grasses were generally more involved in competitive interactions whereas legumes were more involved in facilitative interactions. Under longer drought, species affinity for nutrient rich or wet environments resulted in more negative direct interactions or HOIs, respectively. We conclude that higher-order interactions, crucially depending on species identity, only partially stabilize community dynamics under increasing weather persistence.</p>
Data from: Higher-order species interactions cause time-dependent niche and fitness differences: experimental evidence in plant-feeding arthropods
<p><strong>trajectories.csv </strong>(the raw data)</p> <p><strong>id</strong>: replicate identifier<br><strong>variant</strong>: co-existence status ("competition" or "monoculture")<br><strong>day</strong>: day of experiment<br><strong>species</strong>: mite species ("CRM" or "WCM")<br><strong>n</strong>: population density</p> <p> </p> <p><strong>model.R</strong></p> <p>The R script with the GAMM fitted to the trajectory data (the GAMM model is saved as <strong>model.RData</strong>); also produces simulations from this model (saved as <strong>sim.csv</strong>).</p> <p> </p> <p><strong>model.RData</strong></p> <p>The GAMM for growth rates.</p> <p> </p> <p><strong>sim.csv</strong> (simulations from the GAMM)</p> <p><strong>day</strong>: day of experiment<br><strong>spec_var</strong>: combination of co-existence status ("competition" or "monoculture") and species ("CRM" or "WCM")<br><strong>X1:X1000</strong>: population densities simulated from the fitted GAMM (on the log scale)</p> <p> </p> <p><strong>NFD_over_time_monte_carlo_gam.py</strong></p> <p>Python script to compute niche and fitness differences. Takes <strong>sim.csv</strong> (densities over time for different instantiations) and <strong>model.RData</strong> (stores the GAMM from R for the growth rates) as input and generates the file <strong>Data_NFD_monte_carlo_multi_c.csv</strong> which stores the niche and fitness differences computed for these communities.</p> <p> </p> <p><strong>figures.R</strong></p> <p>The R script that produces Figures 2-4.</p> <p> </p> <p><strong>plot_biotic_model.py</strong></p> <p>Python code to generate the figures S3 and S4 showing the simulations of a biotic resource competition model. </p> <p> </p> <p><strong>plot_abiotic_model.py</strong></p> <p>Python code to generate the figures S1 and S2 showing simulations of an abiotic resource competition model. </p>
Data from: Direct and higher-order interactions in plant communities under increasing weather persistence
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Higher-order and distributed synergistic functional interactions encode information gain in goal-directed learning
<p>Dataset used in "Higher-order and distributed synergistic functional interactions encode information gain in goal-directed learning"</p> <p>https://www.biorxiv.org/content/10.1101/2024.09.23.614484v1</p>
Data from: Higher-order interactions capture unexplained complexity in diverse communities
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CTCF depletion uncouples the role of enhancer-promoter interactions and higher-order chromatin hubs in gene regulation during cellular differentiation.
GEO Series GSE263641. Homo sapiens. 137 samples. Type: Other; Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Emergent gene expression responses to drug combinations predict higher-order drug interactions
GEO Series GSE138256. Saccharomyces cerevisiae BY4741. 238 samples. Type: Expression profiling by high throughput sequencing.
CTCF depletion uncouples the role of enhancer-promoter interactions and higher-order chromatin hubs in gene regulation during cellular differentiation [RNA-seq]
GEO Series GSE263639. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
CTCF depletion uncouples the role of enhancer-promoter interactions and higher-order chromatin hubs in gene regulation during cellular differentiation [Tri-C]
GEO Series GSE263640. Homo sapiens. 21 samples. Type: Other.
CTCF depletion uncouples the role of enhancer-promoter interactions and higher-order chromatin hubs in gene regulation during cellular differentiation [Capture-C]
GEO Series GSE263636. Homo sapiens. 8 samples. Type: Other.
CTCF depletion uncouples the role of enhancer-promoter interactions and higher-order chromatin hubs in gene regulation during cellular differentiation [ChIPmentation]
GEO Series GSE263637. Homo sapiens. 42 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Developmentally regulated higher-order chromatin interactions orchestrate B cell fate commitment [Hi-C]
GEO Series GSE85850. Mus musculus. 4 samples. Type: Other.
Developmentally regulated higher-order chromatin interactions orchestrate B cell fate commitment [microarray]
GEO Series GSE85849. Mus musculus. 12 samples. Type: Expression profiling by array.
CTCF depletion uncouples the role of enhancer-promoter interactions and higher-order chromatin hubs in gene regulation during cellular differentiation [Micro-Capture-C]
GEO Series GSE263638. Homo sapiens. 60 samples. Type: Other.
Developmentally regulated higher-order chromatin interactions orchestrate B cell fate commitment
GEO Series GSE85858. Mus musculus. 16 samples. Type: Expression profiling by array; Other.
Lamin A/C restrains replication domain activity through higher-order chromatin structures and PCNA interaction [ATAC-Seq]
GEO Series GSE289473. Homo sapiens. 6 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Lamin A/C restrains replication domain activity through higher-order chromatin structures and PCNA interaction [BRU-Seq]
GEO Series GSE289474. Homo sapiens. 6 samples. Type: Other.
Lamin A/C restrains replication domain activity through higher-order chromatin structures and PCNA interaction [CUT&Tag]
GEO Series GSE289475. Homo sapiens. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
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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.