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2,100 results for “nodes”
Data from: Inferring node dates from tip dates in fossil Canidae: the importance of tree priors
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Raw images for: The narrowing of dendrite branches across nodes follows a well-defined scaling law
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Over-expression of Ki-67 as a predictor of lymph node metastasis in penile cancer patients
<p>In this study, we will look at the association of Ki-67 with lymph node metastasis in patients with penile cancer.</p>
Plasma-MDS and DCAT metadata records for INPTDAT nodes 43 and 98
<p>This dataset contains the the JSON representation of Plasma-MDS version 0.9.1 as well as archival copies of the Plasma-MDS and DCAT metadata records for the datasets "Correlation of helicality and rotation frequency of filaments in the ntAPPJ" (node 43) and "Non-thermal plasma in contact with water: The origin of species" (node98) published in INPTDAT at https://www.inptdat.de.</p>
WarpX Accelerated Nodes Parallel Computing Paper
<p>This dataset contains the inputs, outputs, job submission scripts, and executables<br> used to create the Figures in "Porting WarpX to GPU-accelerated platforms" by A. Myers<br> et. al, submitted to Parallel Computing as part of the ECP Special Issue on Transitioning<br> to Accelerated nodes.</p> <p>These results were obtained using the October, 2020 release tags of WarpX and AMReX,<br> available on Github here:</p> <p> https://github.com/ECP-WarpX/WarpX</p> <p>and here:</p> <p> https://github.com/AMReX-Codes/amrex</p> <p>The following module files were loaded on Summit:</p> <p> 1) hsi/5.0.2.p5 2) xalt/1.2.0 3) lsf-tools/2.0 4) darshan-runtime/3.1.7<br> 5) DefApps 6) cuda/10.1.243 7) gcc/6.4.0 8) spectrum-mpi/10.3.1.2-20200121</p> <p>To use nsight-compute for the roofline plots, we also loaded:</p> <p> nsight-compute/2020.1.2</p> <p>Manifest:</p> <p>BinScan: contains material used to make Figure 1. To generate the figure, use the<br> Jupyter notebook called "bin_size.ipynb".</p> <p>StrongScaling: contains material used to make Figure 5. To generate the figure, use the<br> Jupyter notebook called "strong_scaling.ipynb".</p> <p>WeakScalingCPU: contains material used to make Figure 4. To generate the figure, use the<br> Jupyter notebook called "weak_scaling.ipynb".</p> <p>WeakScalingGPU: contains material used to make Figure 5. To generate the figure, use the<br> Jupyter notebook called "weak_scaling.ipynb".</p> <p>Roofline: contains material used to make the roofline plots (Figures 2 and 3). This<br> includes output generated using nsight-compute with WarpX and python scripts for<br> processing and plotting these output files. These scripts and methodology originally<br> come from Charlene Yang at NERSC. The file "script.sh" was used to generate the<br> profiler output</p>
Lymph node metastases develop through a wider evolutionary bottleneck than distant metastases
<div class="WordSection1"> <p>Genetic diversity among metastases is poorly understood but contains important information about disease evolution at secondary sites. Here we investigate inter- and intra-lesion heterogeneity for two types of metastases that associate with different clinical outcomes: lymph node and distant organ metastases in human colorectal cancer. We develop a rigorous mathematical framework for quantifying metastatic phylogenetic diversity. Distant metastases are typically monophyletic and genetically similar to each other. Lymph node metastases, in contrast, display high levels of inter-lesion diversity. We validate these findings by analyzing 317 multi-region biopsies from an independent cohort of 20 patients. We further demonstrate higher levels of intra-lesion heterogeneity in lymph node than in distant metastases. Our results show that fewer primary tumor lineages seed distant metastases than lymph node metastases, indicating that the two sites are subject to different levels of selection. Thus, lymph node and distant metastases develop through fundamentally different evolutionary mechanisms.</p> </div>
Data from: Effectiveness of phylogenomic data and coalescent species-tree methods for resolving difficult nodes in the phylogeny of advanced snakes (Serpentes: Caenophidia)
Next-generation genomic sequencing promises to quickly and cheaply resolve remaining contentious nodes in the Tree of Life, and facilitates species-tree estimation while taking into account stochastic genealogical discordance among loci. Recent methods for estimating species trees bypass full likelihood-based estimates of the multi-species coalescent, and approximate the true species-tree using simpler summary metrics. These methods converge on the true species-tree with sufficient genomic sampling, even in the anomaly zone. However, no studies have yet evaluated their efficacy on a large-scale phylogenomic dataset, and compared them to previous concatenation strategies. Here, we generate such a dataset for Caenophidian snakes, a group with >2500 species that contains several rapid radiations that were poorly resolved with fewer loci. We generate sequence data for 333 single-copy nuclear loci with ∼100% coverage (∼0% missing data) for 31 major lineages. We estimate phylogenies using neighbor joining, maximum parsimony, maximum likelihood, and three summary species-tree approaches (NJst, STAR, and MP-EST). All methods yield similar resolution and support for most nodes. However, not all methods support monophyly of Caenophidia, with Acrochordidae placed as the sister taxon to Pythonidae in some analyses. Thus, phylogenomic species-tree estimation may occasionally disagree with well-supported relationships from concatenated analyses of small numbers of nuclear or mitochondrial genes, a consideration for future studies. In contrast for at least two diverse, rapid radiations (Lamprophiidae and Colubridae), phylogenomic data and species-tree inference do little to improve resolution and support. Thus, certain nodes may lack strong signal, and larger datasets and more sophisticated analyses may still fail to resolve them.
GBIF data summaries: GBIF national node type records: France
GBIF—the Global Biodiversity Information Facility—is an international network and research infrastructure funded by the world__s governments and aimed at providing anyone, anywhere, open access to data about all types of life on Earth. <p></p>https://www.gbif.org
PPARγ-bla dataset curated and enriched using the Enalos tools and Enalos KNIME nodes for machine learning analysis (SCENARIOS project)
<p>A curated and enriched dataset for PPARγ-bla, intended for in silico model development, was obtained from PubChem BioAssay under the numeric identifier AID 743194 using Enalos tools and Enalos KNIME nodes. This dataset specifically utilizes compounds from the Tox21 10K chemical library that underwent screening against the PPARγ-bla HEK293H cell line. The cell line contains a beta-lactamase reporter gene, and all the information was extracted from PubChem Bioassay ID 743194 using Enalos tools and Enalos KNIME nodes. The original bioassay, consisting of 6587 compounds, assessed the antagonist activity of small molecules and classified them as 'active', 'inactive' or 'inconsistent' based on their AC50 (potency) score. The curated PPARγ dataset comprises 1230 compounds selected from the original bioassay and enriched with 777 molecular descriptors extracted from their 2D structure using EnalosMold2 KNIME nodes.</p>
Daily profiles (2020) of load of a electricity distribution network (40 nodes) from Croatia – ATTEST project
<p>This dataset was prepared under the framework of the ATTEST project, financed by the European Commission with grant number 864298. The dataset contains information about a real Distribution network, totally anonymized, located in Croatia as in 2020. A network file (including grid topology, nodes, generators, consumption, all of which connected by power lines or transformers) and auxiliary files are provided. The network file (MatPower format) includes a “snapshot” or “steady-state” at a given time with a converged power flow solution. The grid, which is operated at 400 V, 35 kV, 20 kV and 10 kV, has 40 nodes, 59 branches and 14 generators modelled as negative loads. The auxiliary load data comprises 12 typical days representing the combination of each season and the type of day (business day, Saturday, Sunday) gathering the active and reactive consumption at specific feeders of the network in intervals of 15 minutes. Besides, a single line diagram of the network is also provided.</p>
Daily profiles (2020) of load of a electricity distribution network (25 nodes) from Croatia – ATTEST project
<p>This dataset was prepared under the framework of the ATTEST project, financed by the European Commission with grant number 864298. The dataset contains information about a real Distribution network, totally anonymized, located in Croatia as in 2020. A network file (including grid topology, nodes, generators, consumption, all of which connected by power lines or transformers) and auxiliary files are provided. The network file (MatPower format) includes a “snapshot” or “steady-state” at a given time with a converged power flow solution. The grid, which is operated at 110 kV, 35 kV, 20 kV and 10 kV, has 25 nodes, 34 branches and 107 generators modelled as negative loads. The auxiliary load data comprises 12 typical days representing the combination of each season and the type of day (business day, Saturday, Sunday) gathering the active and reactive consumption at specific feeders of the network in intervals of 15 minutes. Besides, a single line diagram of the network is also provided.</p>
Daily profiles (2020) of load of a electricity distribution network (24 nodes) from Croatia – ATTEST project
<p>This dataset was prepared under the framework of the ATTEST project, financed by the European Commission with grant number 864298. The dataset contains information about a real Distribution network, totally anonymized, located in Croatia as in 2020. A network file (including grid topology, nodes, generators, consumption, all of which connected by power lines or transformers) and auxiliary files are provided. The network file (MatPower format) includes a “snapshot” or “steady-state” at a given time with a converged power flow solution. The grid, which is operated at 110 kV, 35 kV, 10 kV and 400 V, has 24 nodes, 32 branches and 2 generators modelled as negative loads. The auxiliary load data comprises 12 typical days representing the combination of each season and the type of day (business day, Saturday, Sunday) gathering the active and reactive consumption at specific feeders of the network in intervals of 15 minutes. Besides, a single line diagram of the network is also provided.</p>
Daily profiles (2020) of load of a electricity distribution network (26 nodes) from Croatia – ATTEST project
<p>This dataset was prepared under the framework of the ATTEST project, financed by the European Commission with grant number 864298. The dataset contains information about a real Distribution network, totally anonymized, located in Croatia as in 2020. A network file (including grid topology, nodes, generators, consumption, all of which connected by power lines or transformers) and auxiliary files are provided. The network file (MatPower format) includes a “snapshot” or “steady-state” at a given time with a converged power flow solution. The grid, which is operated at 220 kV, 110 kV, 35 kV, 10 kV and 400 V, has 26 nodes, 32 branches and 97 generators modelled as negative loads. The auxiliary load data comprises 12 typical days representing the combination of each season and the type of day (business day, Saturday, Sunday) gathering the active and reactive consumption at specific feeders of the network in intervals of 15 minutes. Besides, a single line diagram of the network is also provided.</p>
Part of the electricity transmission system from Croatia (10 nodes)
<p>This dataset was prepared under the framework of the ATTEST project, financed by the European Commission with grant number 864298. The dataset contains information about part of the real Transmission grid, totally anonymized, located in Croatia as in 2020. Two types of network files (including grid topology, nodes, generators, consumption, all of which connected by power lines or transformers) are provided. The network files (MatPower and PSS/E formats) includes a “snapshot” or “steady-state” at a given time with a converged power flow solution. The grid, which is operated at 400 kV, 220 kV, and 110, has 10 nodes, 22 branches and 4 generators.</p>
Daily profiles (2020) of load of a electricity distribution network (86 nodes) from Croatia
<p>This dataset was prepared under the framework of the ATTEST project, financed by the European Commission with grant number 864298. The dataset contains information about a real Distribution network, totally anonymized, located in Croatia as in 2020. A network file (including grid topology, nodes, generators, consumption, all of which connected by power lines or transformers) and auxiliary files are provided. The network file (MatPower format) includes a “snapshot” or “steady-state” at a given time with a converged power flow solution. The grid, which is operated at 10 kV, has 86 nodes, 87 branches and 4 generators modelled as negative loads. The auxiliary load data comprises 12 typical days representing the combination of each season and the type of day (business day, Saturday, Sunday) gathering the active and reactive consumption at specific feeders of the network in intervals of 15 minutes. Besides, a single line diagram of the network is also provided.</p>
Part of the electricity transmission system from Croatia (29 nodes)
<p>This dataset was prepared under the framework of the ATTEST project, financed by the European Commission with grant number 864298. The dataset contains information about part of the real Transmission grid, totally anonymized, located in Croatia as in 2020. Two types of network files (including grid topology, nodes, generators, consumption, all of which connected by power lines or transformers) are provided. The network files (MatPower and PSS/E formats) includes a “snapshot” or “steady-state” at a given time with a converged power flow solution. The grid, which is operated at 400 kV, 220 kV, and 110, has 29 nodes, 44 branches and 13 generators.</p>
Part of the electricity transmission system from Croatia (31 nodes)
<p>This dataset was prepared under the framework of the ATTEST project, financed by the European Commission with grant number 864298. The dataset contains information about part of the real Transmission grid, totally anonymized, located in Croatia as in 2020. Two types of network files (including grid topology, nodes, generators, consumption, all of which connected by power lines or transformers) are provided. The network files (MatPower and PSS/E formats) includes a “snapshot” or “steady-state” at a given time with a converged power flow solution. The grid, which is operated at 400 kV, 220 kV, 110 kV and 35 kV, has 31 nodes, 45 branches and 11 generators. The current state of the grid may lead to congestion and voltage problems.</p>
Fig. 2. Maximum Likelihood tree for genus Fusicolla with RPB2 dataset. Node numbers indicate bootstrap value above 70 in First report of seven unrecorded bambusicolous fungi in Korea
Fig. 2. Maximum Likelihood tree for genus Fusicolla with RPB2 dataset. Node numbers indicate bootstrap value above 70%. Blue colored name indicates the strains isolated in this study. Type strains are indicated by "T".
NanoString dataset for study: Real-time ex vivo perfusion of human lymph nodes invaded by cancer (REPLICANT): a feasibility study
<p>Raw NanoString data for study DOI:10.1002/path.5367</p>
Data from: Tips and nodes are complimentary not competing approaches to the calibration of molecular clocks
Molecular clock methodology provides the best means of establishing evolutionary timescales, the accuracy and precision of which remain reliant on calibration, traditionally based on fossil constraints on clade (node) ages. Tip calibration has been developed to obviate undesirable aspects of node calibration, including the need for maximum age constraints that are invariably very difficult to justify. Instead, tip calibration incorporates fossil species as dated tips alongside living relatives, potentially improving the accuracy and precision of divergence time estimates. We demonstrate that tip calibration yields node calibrations that violate fossil evidence, contributing to unjustifiably young and ancient age estimates, less precise and (presumably) accurate than conventional node calibration. However, we go on to show that node and tip calibrations are complementary, producing meaningful age estimates, with node minima enforcing realistic ages and fossil tips interacting with node calibrations to objectively define maximum age constraints on clade ages. Together, tip and node calibrations may yield evolutionary timescales that are better justified, more precise and accurate than either calibration strategy can achieve alone.
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.