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608 results for “ensembles”
Ensemble BLUP, Machine Learning, and Deep Learning Models Predict Maize Yield Better Than Each Model Alone.
<p>Data and scripts exploring ensembling strategies using the models developed in <a href="https://academic.oup.com/g3journal/advance-article/doi/10.1093/g3journal/jkad006/6982634">Kick et al., 2023</a> (see also <a href="https://zenodo.org/record/7401113">1</a>, <a href="https://zenodo.org/record/6916775">2</a>). Download all files to a single directory then run setup.sh or manually unzip using tar.</p> <p> </p> <table> <tbody> <tr> <td><strong>Filename</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>setup.sh</td> <td>Simple script that unzips zipped directories</td> </tr> <tr> <td>ext_data</td> <td>Reduced data from Kick et al. 2023</td> </tr> <tr> <td>ext_data_notebooks</td> <td>Contains python notebooks containing analysis and R markdown file containing visualization of results. Python and R data objects are written to allow results to be read in instead of re-generated.</td> </tr> <tr> <td>output</td> <td>Folder containing a placeholder file.</td> </tr> </tbody> </table> <p> </p> <p>This research used resources provided by the United States Department of Agriculture’s Agricultural Research Service (project number 5070-21000-041-000-D). The SCINet project of the USDA Agricultural Research Service (project number 0500-00093-001-00-D) was instrumental in the training of the models used in this work. In addition, we would like to acknowledge those presently and historically involved in generating data for the Genomes to Fields Initiative.</p> <p> </p> <p> </p> <p> </p>
Inhibitory silencing enhances encoding precision of neuronal ensembles
<p>Neuronal ensembles are structured groups of coactive neurons associated with motor, sensory, and behavioral functions. However, how ensembles encode information remains unclear. To explore this, we investigated the responses of layer 2/3 visual cortical neurons in awake mice using two-photon volumetric calcium imaging during visual stimulation. We detected neuronal ensembles employing an unsupervised model-free algorithm. In response to visual stimuli, ensembles exhibited small trial-to-trial variability and high orientation selectivity. During an ensemble occurrence, besides neurons that were significantly activated by the stimulus, we also found neurons whose activity was significantly decreased in response. To distinguish between these two groups of neurons, we introduced the term "onsemble" for the significantly active neurons and "offsemble" for the silenced ones. Calcium decay kinetics in offsemble neurons significantly decreased during stimulus presentation, indicative of selective inhibition. Ensembles predicted visual stimulus orientation better than averaging the activity of individual onsemble or offsemble neurons. We conclude that the combined activation and inhibition of onsemble and offsemble neurons enhances visual encoding. Therefore, ensembles could be functional units representing information in cortical circuits, combining selectively activated and silenced neurons as an emergent and distributed neural code.</p>
Pairwise residue-residue Euclidean distances for a Histatin-5 ensemble
<p>Pairwise residue-residue Euclidean distances for a pair of independent replicas of the protein ensemble Histatin-5.</p><p>Each file corresponds to a n x p matrix, where n is the number of conformers and p is the number of pairwise inter-residue distances, that is, p = L(L-1)/2 where L is the number of sequence residues. Each row corresponds to a p-vector of distances featuring the corresponding conformation. Distances are computed between CB atoms (CA for glycines) and are given in Angstroms (Å).</p><p>Conformations were generated using Flexible-Meccano (Ozenne et al. 2012, Bernado et al. 2005) and refined using previously reported small-angle X-ray scattering (SAXS) data (Sagar et al. 2021).</p>
K-model and H-gradient model ensemble averaged data (Version 1)
<p>It is the ensemble averaged data used in the creation of the manuscript "The impact of subgrid-scale turbulence model on tropical cyclone dynamics in convection-permitting simulations"</p>
Recognition of sounds by ensembles of proteinoids
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Neural ensemble reactivation in REM and SWS coordinate with muscle activity to promote rapid motor skill learning
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Surrogate flash flooding: Probabilistic excessive rainfall predictions from the High Resolution Ensemble Forecast (HREF) system
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Data from: Bat ensembles differ in response to use zones in a tropical biosphere reserve
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An ensemble machine learning bioavailable strontium isoscape for Eastern Canada
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Data for: Ensemble-based data assimilation of significant wave height from Sofar Spotters and satellite altimeters with a global operational wave model
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Pin1 two-state structural ensembles of apo, FFpSPR-bound and pCDC25c-bound form
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Data from: STREAM-Sat: a novel near-realtime quasi-global satellite-only ensemble precipitation
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Long-term stability of cortical ensembles
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SNP genotype and hyperspectral reflectance data from: Ensembles of genomic and hyperspectral imaging-based prediction enable selection for reduced deoxynivalenol content in wheat grains
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Data from: Incorporating abundance information and guiding variable selection for climate-based ensemble forecasting of species' distributional shifts
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Coordinates activities of retrosplenial ensembles during resting-state encode spatial landmarks. Part 1 of 2
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Coordinates activities of retrosplenial ensembles during resting-state encode spatial landmarks. Part 2 of 2
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Ensemble synchronization in the reassembly of Hydra's nervous system
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Intermittent rate coding and cue-specific neuronal ensembles support working memory
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Data for: Learning in ensembles of proteinoid microspheres
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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.