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105
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ShareScore release 0.9.0
Dataset results
105 results for “temporal networks”
Robot-induced hallucinations in Parkinson's disease depend on altered sensorimotor processing in fronto-temporal network
<p>Dataset of the fMRI study in healthy subjects from "Robot-induced hallucinations in Parkinson’s disease depend on altered sensorimotor processing in fronto-temporal network"</p> <p>It contains the fMRI data from the healthy subjects that performed the robotic stimulation task inducing the presence hallucination.</p>
Pollen transport networks reveal highly diverse and temporally stable plant-pollinator interactions in an Appalachian floral community
<p>Floral visitation alone has been typically used to characterize plant-pollinator interaction networks even though it ignores differences in the quality of floral visits (e.g. transport of pollen) and thus may overestimate the number and functional importance of pollinating interactions. However, how network structural properties differ between floral visitation and pollen transport networks is not well understood. Furthermore, the strength and frequency of plant-pollinator interactions may vary across fine temporal scales (within a single season) further limiting our predictive understanding of the drivers and consequences of plant-pollinator network structure. Thus, evaluating the structure of pollen transport networks and how they change within a flowering season may help increase our predictive understanding of the ecological consequences of plant-pollinator network structure. Here we compare plant-pollinator network structure using floral visitation and pollen transport data and evaluate within-season variation in pollen transport network structure in a diverse plant-pollinator community. Our results show that pollen transport networks provide a more accurate representation of the diversity of plant-pollinator interactions in a community but that floral visitation and pollen transport networks do not differ in overall network structure. Pollen transport network structure was relatively stable throughout the flowering season despite changes in plan and pollinator species composition. Overall, our study highlights the need to improve our understanding of the drivers of plant-pollinator network structure in order to more fully understand the process that govern the assembly of these interactions in nature.</p>
Data Repository for "Integrating Water Quality Data with a Bayesian Network Model to Improve Spatial and Temporal Phosphorus Attribution: Application to the Maumee River Basin"
<p>Data for "Integrating Water Quality Data with a Bayesian Network Model to Improve Spatial and Temporal Phosphorus Attribution: Application to the Maumee River Basin". This repository contains all the processed data used in the simulation (in "processed" folder), part of the raw data (in "raw" folder), and the SWAT simulation results (in "SWAT" folder). The code for processing the raw data, which are either provided here or publicly available online, is provided in the <a href="https://doi.org/10.5281/zenodo.8132662">code repository</a>. The links to the publicly available raw data are also provided in the code repository.</p>
Focal mechanisms and hypocenter locations detected by temporal deployed seismic networks in and around hypocentral area of the 2000 Western Tottori Earthquake
<p>Hypocenter and focal mechanism data in the hypocentral area of the 2000 Western Tottori Earthquake. Detailed description of the datafiles is in README.docx.</p>
Data from: Temporal stability in a male African elephant social network
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Pollen transport networks reveal highly diverse and temporally stable plant-pollinator interactions in an Appalachian floral community
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Data from: Evolution of transcription networks in response to temporal fluctuations
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Data from: The temporal dimension in individual-based plant pollination networks
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A comprehensive temporal patterning gene network in Drosophila medulla neuroblasts revealed by single-cell RNA sequencing
GEO Series GSE168553. Drosophila melanogaster. 2 samples. Type: Expression profiling by high throughput sequencing.
A temporal shift in regulatory networks and pathways in the bovine small intestine during Cooperia oncophora infection
GEO Series GSE11950. Bos taurus. 20 samples. Type: Expression profiling by array.
Dissecting the temporal genetic networks programming soybean embryo development from embryonic morphogenesis to post-germination
GEO Series GSE248224. Glycine max. 46 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome dynamics of developing photoreceptors in 3-D retina cultures recapitulates temporal sequence of human cone and rod differentiation revealing cell surface markers and gene networks
GEO Series GSE67645. Homo sapiens. 23 samples. Type: Expression profiling by high throughput sequencing.
Temporal profiling and network analysis of rhythmic gene expression and novel functional gene annotation in the water flea, Daphnia pulex
GEO Series GSE67781. Daphnia pulex. 24 samples. Type: Expression profiling by array.
A spatio-temporally constrained gene regulatory network directed by PBX1/2 acquires limb patterning specificity via HAND2 [ATAC-seq]
GEO Series GSE197855. Mus musculus. 3 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Temporal-spatial Establishment of Initial Niche for the Primary Spermatogonial Stem Cell formation is Determined by an ARID4B Regulatory Network
GEO Series GSE84808. Mus musculus. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Temporal-spatial Establishment of Initial Niche for the Primary Spermatogonial Stem Cell formation is Determined by an ARID4B Regulatory Network (ChIP-Seq)
GEO Series GSE84802. Mus musculus. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Gene coexpression network and community detection analyses of CA3 trascriptome reveal distinct pathogenic and compensatory pathways in early and late onset febrile forms of temporal lobe epilepsy
GEO Series GSE57585. Homo sapiens. 14 samples. Type: Expression profiling by array.
The RNA interactomes of Imp and Syp reveal temporal RNA regulatory network in Drosophila brain development
GEO Series GSE262499. Drosophila melanogaster. 23 samples. Type: Other.
Network analysis identifies temporal regulation of transcriptomic and physiological responses to early drought perception in Brassica rapa.
GEO Series GSE90841. Brassica rapa. 48 samples. Type: Expression profiling by high throughput sequencing.
Gene regulatory networks controlling temporal patterning, neurogenesis, and cell fate specification in the mammalian retina.
GEO Series GSE181251. Mus musculus. 38 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
ScienceDex guides
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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.