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ShareScore release 0.9.0
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151 results for “network scaling”
Ecological network complexity scales with area
<p><span><span><span><span><span><span><span><span><span><span><span>Larger geographical areas contain more species–an observation raised to a law in ecology. Less explored is whether biodiversity changes are accompanied by a modification of interaction networks. We use data from 32 spatial interaction networks from different ecosystems to analyse how network structure changes with area. We find that basic community structure descriptors (number of species, links, and links per species) increase with area following a power-law. Yet, the distribution of links per species varies little with area, indicating that the fundamental organization of interactions within networks is conserved. Our null model analyses suggest that the spatial scaling of network structure is determined by factors beyond species richness and the number of links. We demonstrate that biodiversity–area relationships can be extended from species counts to higher levels of network complexity. Therefore, the consequences of anthropogenic habitat destruction may extend from species loss to wider simplification of natural communities.</span></span></span></span></span></span></span></span></span></span></span></p>
Supporting Information: Environmental benefits of large-scale second-generation bioethanol production in the EU: An integrated supply chain network optimization and Life Cycle Assessment approache
<p>This supporting information provides all input data of the model, the assumptions made and the literature and database references for the publication<em> Environmental benefits of large-scale second-generation bioethanol production in the EU: An integrated supply chain network optimization and Life Cycle Assessment approache</em>. The environmental data is based on life cycle assessments, with full information on the life cycle inventory and the results of the life cycle impact assessment based on the ReCiPe method. It also includes detailed results for all objective functions in all scenarios (optimization of 18 midpoints, 3 endpoints, and economic optimization in 5 tax scenarios and 2 feedstock scenarios), and detailed results of the sensitivity analysis and Pareto optimization.</p>
Supporting Information for "First Observations of Large Scale Traveling Ionospheric Disturbances Using Automated Amateur Radio Receiving Networks"
<p><strong>Introduction</strong></p> <p>The supporting information for this paper consists of a movie version of Figure 2 in the main paper, comparing the high frequency (HF) amateur radio observations to differential Global Navigation Satellite System (GNSS) Total Electron Content (TEC) measurements. In this revised version of the repository, the TEC data has been reprocessed such that all GNSS data with elevation angles down to 10 degrees were kept when applying the Savitzky–Golay (SG) filter. After the SG filter was applied, data with elevation angles below 30 degrees were discarded. This was done to remove artifacts observed in the original movies.</p> <p> </p> <p><strong>Movie S1 (20171103 Ham and TEC LSTID.mp4)</strong></p> <p>(Top Panel) Time series showing the TX-RX distance for 14 MHz amateur radio spots in 2 min by 25 km bins from 1200 UT 3 Nov 2017 - 0000 UT 4 Nov 2017. (Bottom Panel) differential Global Navigation Satellite System (GNSS) Total Electron Content (TEC) measurements over the Continental United States corresponding to the times indicated by the moving white vertical line in the top panel.</p> <p> </p> <p><strong>Movie S2 (20171103 Ham and TEC LSTID – With Arrow.mp4)</strong></p> <p>Same as movie S1, but with a fiducial black arrow indicating an estimated LSTID horizontal wavelength of 1681 km and propagation azimuth of 163°.</p>
Deploying Near Optimal Delay Constrained Paths with Segment-Routing in Massive Scale Networks
<p>Dataset consisting of 5 large topologies used for the evaluation of Best2cop - multi-area version. <br> <br> The topologies themselves are written as a list of edges following the format : <br> <strong>source target delay cost area</strong> <br> "cost" being the IGP cost of the link, and "area", the IGP area to which the edge belongs.</p> <p>Each topology has a descriptive file showcasing some of the network's properties (density, diameter...) as well as an HTML file allowing to see the topology on an actual world map. Note that while we consider the road infrastructure, the links are represented in an abstract fashion for readability purposes.</p> <p> </p>
Systematic dissection of transcriptional regulatory networks by genome-scale and single-cell CRISPR screens
Millions of putative transcriptional regulatory elements (TREs) have been cataloged in the human genome, yet their functional relevance in specific pathophysiological settings remains to be determined. This is critical to understand how oncogenic transcription factors (TFs) engage specific TREs to impose transcriptional programs underlying malignant phenotypes. Here, we combine cutting edge CRISPR screens and epigenomic profiling to functionally survey ≈15,000 TREs engaged by estrogen receptor (ER). We show that ER exerts its oncogenic role in breast cancer by engaging TREs enriched in GATA3, TFAP2C, and H3K27Ac signal. These TREs control critical downstream TFs, among which TFAP2C plays an essential role in ER-driven cell proliferation. Together, our work reveals novel insights into a critical oncogenic transcription program and provides a framework to map regulatory networks, enabling to dissect the function of the noncoding genome of cancer cells.
Multi-scale full waveform inversion based on a convolutional neural network
<p>The research data from this paper are uploaded here and are available for download.</p>
Improving rainfall forecast at the district scale over the eastern Indian region using deep neural network
<p>The code contains ANN and CNN models.</p>
Interpreting Cis-Regulatory Interactions from Large-Scale Deep Neural Networks for Genomics
<p>Results and code to replicate analysis in "Interpreting Cis-Regulatory Interactions from<br> Large-Scale Deep Neural Networks for Genomics" by Toneyan and Koo.</p>
The Influence of Multi-domain Cognitive Training on Large-scale Structural and Functional Brain Networks in MCI
ClinicalTrials.gov study NCT03883308. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Multi-scale Modeling of Sleep Behaviors in Social Networks
ClinicalTrials.gov study NCT02846077. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
The Evaluation With Artificial Neural Network of Pain Scales in Children (ANN)
ClinicalTrials.gov study NCT02682875. IPD Sharing: YES. Countries: 1. Publications: 1.
Data from: Scale-dependent genetic structure of the Idaho giant salamander (Dicamptodon aterrimus) in stream networks
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Data from: Functional outcomes of mutualistic network interactions: a community-scale study of frugivore gut passage on germination
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Data from: Benefits and challenges of scaling up expansion of marine protected area networks in the Verde Island Passage, Central Philippines
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Data from: Integrated genome-scale analysis identifies novel genes and networks underlying senescence in maize
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Data from: Fine-scale population structure and riverscape genetics of brook trout (Salvelinus fontinalis) distributed continuously along headwater channel networks
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Data from: Chromosome-scale inference of hybrid speciation and admixture with convolutional neural networks
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Data from: Network-scale effects of invasive species on spatially-structured amphibian populations
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Large-scale metabolic interaction network of the mouse and human gut microbiota
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Data from: Frugivore biodiversity and complementarity in interaction networks enhance landscape-scale seed dispersal function
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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.