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144
datasets available to search
ShareScore release 0.7.1
Dataset results
144 results for “complex network”
Data from: Nonlinear growth: an origin of hub organization in complex networks
Many real-world networks contain highly connected nodes called hubs. Hubs are often crucial for network function and spreading dynamics. However, classical models of how hubs originate during network development unrealistically assume that new nodes attain information about the connectivity (for example the degree) of existing nodes. Here, we introduce hub formation through nonlinear growth where the number of nodes generated at each stage increases over time and new nodes form connections independent of target node features. Our model reproduces variation in number of connections, hub occurrence time, and rich-club organization of networks ranging from protein–protein, neuronal and fibre tract brain networks to airline networks. Moreover, nonlinear growth gives a more generic representation of these networks compared with previous preferential attachment or duplication–divergence models. Overall, hub creation through nonlinear network expansion can serve as a benchmark model for studying the development of many real-world networks.
Deep Neural Network Surrogate for Surface Complexation Model of Metal Oxide/Electrolyte Interface
<p>These files are the data used in the paper "<a href="https://scholar.google.com/citations?view_op=view_citation&hl=en&user=ncAYQ4MAAAAJ&sortby=pubdate&citation_for_view=ncAYQ4MAAAAJ:LkGwnXOMwfcC">Deep neural network surrogate for surface complexation model of metal oxide/electrolyte interface</a>".</p> <ul> <li>CSV files are used to train the DNN model.</li> <li>NPZ files are used to train the random forest model. </li> </ul>
Water networks in complexes between proteins and FDA-approved drugs
<p>Dataset to accompany manuscript - prepared protein-ligand complexes</p>
Network Model with Internal Complexity Bridges Artificial Intelligence and Neuroscience
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Physics-informed Partitioned Coupled Neural Operator for Complex Networks Datasets
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Data from: Environmentally induced changes in correlated responses to selection reveal variable pleiotropy across a complex genetic network
Selection in novel environments can lead to a coordinated evolutionary response across a suite of characters. Environmental conditions can also potentially induce changes in the genetic architecture of complex traits, which in turn could alter the pattern of the multivariate response to selection. We describe a factorial selection experiment using the nematode Caenorhabditis remanei in which two different stress-related phenotypes (heat and oxidative stress resistance) were selected under three different environmental conditions. The pattern of covariation in the evolutionary response between phenotypes or across environments differed depending on the environment in which selection occurred, including asymmetrical responses to selection in some cases. These results indicate that variation in pleiotropy across the stress response network is highly sensitive to the external environment. Our findings highlight the complexity of the interaction between genes and environment that influences the ability of organisms to acclimate to novel environments. They also make clear the need to identify the underlying genetic basis of genetic correlations in order understand how patterns of pleiotropy are distributed across complex genetic networks.
Data from: How new concepts become universal scientific approaches – insights from citation network analysis of agent-based complex systems science
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Data from: A model to identify urban traffic congestion hotspots in complex networks
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Data from: Environmental complexity influences association network structure and network-based diffusion of foraging information in fish shoals
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Data from: Nonlinear growth: an origin of hub organization in complex networks
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Data from: Network analyses reveal intra- and interspecific differences in behaviour when passing a complex migration obstacle
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Data from: Modeling the internet of things, self-organizing and other complex adaptive communication networks: a cognitive agent-based computing approach
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Data from: Maximum parsimony inference of phylogenetic networks in the presence of polyploid complexes
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Data from: Environmentally induced changes in correlated responses to selection reveal variable pleiotropy across a complex genetic network
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Genome-wide distribution of AdpA, a global regulator for secondary metabolism and morphological differentiation in Streptomyces, revealed the extent and complexity of the AdpA regulatory network.
GEO Series GSE33994. Streptomyces griseus. 9 samples. Type: Expression profiling by array; Genome binding/occupancy profiling by high throughput sequencing.
INO80 complex in the core regulatory network governing ESC self-renewal [771_timecourse]
GEO Series GSE49250. Mus musculus. 12 samples. Type: Expression profiling by array.
An RNAi Screen for Skin Morphogenesis Unravels The Complexities of Rho GTPase Networks
GEO Series GSE123047. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Opaque-2 regulates a complex gene network associated with cell differentiation and storage function of maize endosperm
GEO Series GSE114343. Zea mays. 10 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
INO80 complex in the core regulatory network governing ESC self-renewal [ChIP-Seq]
GEO Series GSE49137. Mus musculus. 12 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Deciphering the Fur transcriptional regulatory network highlights its complex role beyond iron metabolism in Escherichia coli [RNA-seq]
GEO Series GSE54900. Escherichia coli str. K-12 substr. MG1655. 8 samples. Type: Expression profiling by high throughput sequencing.
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.