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1,773 results for “Predictive model”
Data from: Predicting the genetic impact of stocking in Brook Charr (Salvelinus fontinalis) by combining RAD sequencing and modeling of explanatory variables
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Data from: A simple behavioral model predicts the emergence of complex animal hierarchies
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Data from: Mainland size variation informs predictive models of exceptional insular body size change in rodents
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Data from: Using viromes to predict novel immune proteins in non-model organisms
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Data from: Comparison of seven simple loss models for runoff prediction at the plot, hillslope and catchment scale in the semiarid southwestern U.S.
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Data from: Repertoire-wide gene structure analyses: a case study comparing automatically predicted and manually annotated gene models
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Delta-X: NUMAR Predictive Model for Marsh Accretion Rates and Chemical Properties
This dataset provides input data and model code to run the Marsh Accretion Rates (NUMAR) process model used to predict soil accretion rates and chemical properties for marsh sites in the Mississippi River Delta. NUMAR is a modification of the NUMAN model by Chen and Twilley (1999) that was developed for mangrove environments. This dataset provides Python code, input data in comma separated values (CSV) format, and documentation for installing and running the model in Portable Document Format (PDF).
MODIS Aqua L2 model predicted low cloud types of chopped blocks in which low cloud dominates (block size: 128pixels x 128pixels) V001 (MYD_L2_MPLCT) at GES DISC
This product is composed of a beta version for a product from the MODerate resolution Imaging Spectrometer (MODIS) on board the Aqua satellite.This dataset contains model predicted low cloud morphology type classifications (MPLCT) of each of the chopped blocks as part of our global MODIS Aqua data from the 2017 MEaSUREs project, A Comprehensive Data Record of Marine Low-level and Deep Convective Cloud Systems Using an Object-Oriented Approach.These data are the model predictions of cloud types for low-cloud-dominated blocks over the oceans for individual MODIS Aqua granule data, chopped into small blocks in shape (np_x, np_y), where np_x = 128 pixels and np_y = 128 pixels. These low-cloud-dominated blocks are defined by the conditions: the ratio of high-cloud fraction and low-cloud fraction is smaller than 0.2, with high-cloud fraction < 0.3 and low-cloud fraction > 0.05. Only daytime granule data are included and blocks with sensor zenith angle > 45 and blocks over land are excluded.The variables include:block_low: the name of the low-cloud-dominated block, based on which the location of the chopped block in the granule data can be found.pred_cat: the predicted cloud type of each block.pred_prob: the prediction probability of cloud typelcf: the low-cloud fraction of the low-cloud-dominated block.sensor_zenith: the sensor zenith angle at the center of the low-cloud-dominated blockFive latitude and longitude points for the four corners and center of the chopped blocksThe DOIs of the related datasets in this project are:MYD_L2_CB_001 DOI: 10.5067/DFDGJR6707D8MYD_L3_OFLCT_001 DOI: 10.5067/3FAIC739DQRH
CLPX-Model: Local Analysis and Prediction System: 4-D Atmospheric Analyses, Version 1
The Local Analysis and Prediction System (LAPS), run by the NOAA's Forecast Systems Laboratory (FSL), combines numerous observed meteorological data sets into a collection of atmospheric analyses.
Characterizing the Tumor Immune Microenvironment of Syngeneic Mouse Models of Ovarian Cancer to Predict Response to PD-L1 blockade
GEO Series GSE183368. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Model-to-crop conserved NUE Regulons enhance machine learning predictions of nitrogen use efficiency
GEO Series GSE280344. Zea mays. 57 samples. Type: Expression profiling by high throughput sequencing.
Cross species transcriptomic signatures predict response to MK2 inhibition in mouse models of chronic inflammation
GEO Series GSE164339. Mus musculus. 44 samples. Type: Expression profiling by high throughput sequencing.
A six-gene prediction model for tumor response to induction chemotherapy in locoregionally advanced laryngo-hypopharyngeal carcinoma
GEO Series GSE184072. Homo sapiens. 54 samples. Type: Expression profiling by high throughput sequencing.
From gene expression to pregnancy prediction: towards precision ART through systems biology and Bayesian modeling
GEO Series GSE297368. Homo sapiens. 43 samples. Type: Expression profiling by high throughput sequencing; Third-party reanalysis.
Identification of Potential Models for Predicting Progestin Insensitivity in Patients with Endometrial Atypical Hyperplasia and Endometrial Cancer Based on Integration of ATAC-Seq and RNA-Seq Analysis
GEO Series GSE201926. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Machine-learning model based on glycosyltransferase expression predicts multiple cancer types, subtypes and survival probability
GEO Series GSE254461. Homo sapiens. 57 samples. Type: Expression profiling by high throughput sequencing.
HydRA: Deep-learning models for predicting RNA-binding capacity from protein interaction association context and protein sequence
GEO Series GSE221870. Homo sapiens. 76 samples. Type: Other.
Skin transcriptomics predict outcome after ionizing radiation exposure with potential dosimetric applications in a mouse model
GEO Series GSE185149. Mus musculus. 82 samples. Type: Expression profiling by array.
Lineage-specific iPSC-Derived SMC Modeling Predicts Integrin Alpha-V Antagonism Reduces Aortic Root Aneurysm Formation in Marfan Syndrome Mice
GEO Series GSE223807. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
A humanized Animal Model Predicts Clonal Evolution and Therapeutic Vulnerabilities in Myeloproliferative Neoplasms
GEO Series GSE160927. Homo sapiens. 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.