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Dataset results
209 results for “probabilistic”
Data from: Probabilistic divergence time estimation without branch lengths: dating the origins of dinosaurs, avian flight and crown birds
Open the record for dataset details and reuse information.
Data from: How to measure maturation: a comparison of probabilistic methods used to test for genotypic variation and plasticity in the decision to mature
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Probabilistic Freeze-Thaw Record for the Northern Hemisphere, 2016-2020
This dataset provides a probabilistic freeze/thaw (FT) data record from 2016 to 2020 for the Northern Hemisphere derived using a deep learning model (U-Net). The model was informed by satellite multi-frequency microwave brightness temperature retrievals from the NASA SMAP (Soil Moisture Active Passive) and JAXA AMSR2 (Advanced Microwave Scanning Radiometer 2) radiometers, and trained using daily soil temperature observations from Northern Hemisphere weather stations and global reanalysis data (ERA-5). Unlike other available FT data records that provide only a binary classification of frozen or non-frozen conditions, this product includes both binary FT and continuous variable estimates of the probability of thawed conditions. This product is designed to complement other established binary FT data records, including the NASA FT Earth System Data Record and SMAP Level 3 FT operational products, by providing a probabilistic FT variable with enhanced accuracy and sensitivity to near-surface (<=5 cm depth) soil FT condition. The data are provided in cloud optimized GeoTIFF (COG) format.
A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways
GEO Series GSE68576. Mus musculus. 30 samples. Type: Methylation profiling by high throughput sequencing.
A Probabilistic Model of Transcription Dynamics applied to Estrogen Signalling in Breast Cancer Cells
GEO Series GSE44800. Homo sapiens. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Multi-cell type deconvolution using a probabilistic model of single-molecule DNA methylation haplotypes
GEO Series GSE239605. Homo sapiens. 205 samples. Type: Methylation profiling by high throughput sequencing.
A probabilistic framework for cellular lineage reconstruction using integrated single-cell 5-hydroxymethylcytosine and genomic DNA sequencing
GEO Series GSE131678. Homo sapiens; Mus musculus. 16 samples. Type: Methylation profiling by high throughput sequencing.
A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways [mESCs]
GEO Series GSE68574. Mus musculus. 12 samples. Type: Methylation profiling by high throughput sequencing.
Joint probabilistic modeling of paired transcriptome and proteome measurements in single cells [CITE-seq of mouse spleen and lymph nodes]
GEO Series GSE150599. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing; Other.
A hybrid model for fast and probabilistic urban pluvial flood prediction - dataset
<p>A hybrid model for fast and probabilistic urban pluvial flood prediction - dataset </p> <p>This dataset presents the data used in the paper "A hybrid model for fast and probabilistic urban pluvial flood prediction". Data used to build, calibrate and evaluate the model and data that support the findings of the study are given for two cases, namely Gent and Antwerp. </p> <p>Under the folder of each case, one could find the following content:</p> <ul> <li>Model building: Data used to build the model topology. It includes geo-data of the 1D sewer network, boundary conditions of the catchment and spatial rainfall configurations </li> <li>Calibration: Rainfall data and flood records data used for calibration of the model.</li> <li>Results and evaluation: Rainfall events used for evaluation, flood probability predicted by the hybrid models and flood records used for comparing with the hybrid models. </li> </ul>
Probabilistic Model-Based Analysis to Improve Software Energy Efficiency - Presentation
<p>Presentation</p> <p>Paper: Probabilistic Model-Based Analysis to Improve Software Energy Efficiency</p> <p>SBES 2020 - Research Track</p>
Data from: The ozone radiative forcing of nitrogen oxide emissions from aviation can be estimated using a probabilistic approach.
<p>This dataset accompanies the journal article entitled "The ozone radiative forcing of nitrogen oxide emissions from aviation can be estimated using a probabilistic approach.", currently under review, and contains:</p> <p>1) The post-processed version of the original dataset that is available here [1]: https://data.4tu.nl/private_datasets/cLnjZscxOJDZnBSajrE0XxooMxJspT40byq4FVnq26A. </p> <p>The original dataset has been generated from several simulations performed with the ECHAM/MESSy Atmospheric Chemistry model (EMAC). The short-term impact on atmospheric ozone (O<sub>3</sub>) from aircraft nitrogen oxide (NO<sub>x</sub>) emissions is estimated for five regions (North America, Eurasia, South America, Africa and Australasia), three pressure altitudes (200, 250 and 300 hPa) and two seasons (July 1, 2014 representing the Northern summer and January 1, 2014 representing Northern winter) using three calculation methods: Eulerian tagging, Lagrangian tagging and perturbation. Each region has 28 points at which 0.5 Gg of NO are introduced in the form of a 15-min pulse emission. </p> <p>In our manuscript, we use the Lagrangian tagging dataset. We compute the global annual mean radiative forcing of O<sub>3 </sub>from NO<sub>x </sub>for each and every emission point, and plot them in Figure 1 (b). The mass curves of NO<sub>x </sub>and O<sub>3</sub> for two emission points are also plotted using the original data in Figure 1 (c). </p> <p>2) Meteorological data, fllight path data from EUROCONTROL, great circle data which are plotted in Figure 5 (b) of the manuscript. </p> <p>Please consult the README file for specific details regarding the data.</p>
PyCOMPSs Probabilistic Tsunami Forecast (PTF) - Kos-Bodrum 2017 earthquake and tsunami test-case results
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Mechanistic Exploration and Kinetic Modeling through In-Silico Data Generation and Probabilistic Machine Learning Analysis
<p>This zip file includes the dataset 'two_reactions_022624.csv,' which is used for training and testing ML/DL models in the paper 'Mechanistic Exploration and Kinetic Modeling through In-Silico Data Generation and Probabilistic Machine Learning Analysis,' as well as trained models and some files used for training the model. When running the model downloaded from GitHub, copy and paste the files downloaded from here into the subfolder with the same name and path as the one downloaded from GitHub.</p>
Dataset for "Quantitative evaluation of probabilistic hazard mapping with polynomial chaos quadrature and its practical application"
<p>Dataset for the manuscript entitled "Quantitative evaluation of probabilistic hazard mapping with polynomial chaos quadrature and its practical application" by T. Tanabe, K. Tsunematsu, and K. Nishimura submitted to Journal of Geophysical Research: Earth Surface.</p> <p> </p>
Historical Database for Very-Short-Term Probabilistic Forecasting of System Imbalance
<p>Historical database (2014-2018) for Very-Short-Term Probabilistic Forecasting of System Imbalance.</p> <p>These data are obtained from the Belgian transmission system operator (Elia) and the European Network of Transmission system Operators (ENTSO-E).</p> <p>If you use these data, please refer to the following paper:</p> <p>J. Bottieau, L. Hubert, Z. De Grève, F. Vallée and J-F. Toubeau, “Very-Short-Term Probabilistic Forecasting for Risk-Aware Participation in the Single Price Imbalance Settlement,”.</p>
Out of Control: Reducing Probabilistic Models by Control-Flow Reduction - Experiments
<p>Scripts and benchmark files for reproducing the experiments regarding the reduction of probabilistic models reported in our submission.</p>
On the importance of additional behavioral observation in behavioral psychopharmacology research: a case study on agomelatine's effects on feedback sensitivity in probabilistic reversal learning test in rats
<p>Dataset to the manuscript entitled: On the importance of additional behavioral observation in behavioral psychopharmacology research: a case study on agomelatine's effects on feedback sensitivity in probabilistic reversal learning test in rats.</p>
Impact of Three Probabilistic Antibiotic Therapy on Digestive Microbiota and Colonization With Multi-resistant Bacteria
ClinicalTrials.gov study NCT07058415. IPD Sharing: NO. Countries: 1. Publications: 0.
Effect of Feedback and Practice on Probabilistic Decision Making in Attention Deficit and Hyperactivity Disorder
ClinicalTrials.gov study NCT01574976. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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.