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Dataset results
279 results for “model comparison”
Comparison of the pathogenicity of CA10 with CA16 and EV71 that cause hand, foot and mouth disease in a mouse model
GEO Series GSE237009. Mus musculus. 80 samples. Type: Expression profiling by high throughput sequencing.
RNA-seq comparison of HFD-mTAC model of heart failure with preserved ejection fraction vs control heart tissue in Mus Musculus
GEO Series GSE249409. Mus musculus. 10 samples. Type: Expression profiling by high throughput sequencing.
Comparison of ILC1s and NK cells transcriptomes in subcutaneous tumor model
GEO Series GSE253918. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Comparison of genes related with tertiary lymphoid tissue formation between control and diseased model mice
GEO Series GSE160488. Mus musculus. 6 samples. Type: Expression profiling by array.
Mouse models of CMN and comparison to human CMN
GEO Series GSE199891. Mus musculus. 18 samples. Type: Expression profiling by high throughput sequencing.
Comparison of 7 small cell lung cancer PDX models, cultured ex vivo, for response to LSD1 inhibitor RG6016/ORY1001
GEO Series GSE103095. Homo sapiens. 14 samples. Type: Expression profiling by high throughput sequencing.
Neuronal cell lines as model dorsal root ganglion neurons: a transcriptomic comparison
GEO Series GSE75811. Mus musculus; Homo sapiens; Rattus rattus. 4 samples. Type: Expression profiling by high throughput sequencing.
A comprehensive transcriptomic comparison of hepatocyte model systems
GEO Series GSE214097. Homo sapiens. 10 samples. Type: Expression profiling by high throughput sequencing.
Vascular dysfunction is the primary cause of symptom onset in a mouse model of oxaliplatin-induced peripheral neuropathy: comparison of gene expression in blood vessels from mouse brain and sciatic n
GEO Series GSE255096. Mus musculus. 24 samples. Type: Expression profiling by high throughput sequencing.
Comparison of syngeneic tumor models reveals different tumor microenvironments with distinct subsets of cancer-associated fibroblasts polarized by infiltrating T cells
GEO Series GSE245293. Mus musculus. 23 samples. Type: Expression profiling by high throughput sequencing.
Comparison of two human organoid models of lung and intestinal inflammation reveals Toll-like receptor signalling activation and monocyte recruitment.
GEO Series GSE151796. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
A mouse model of human coronavirus HCoV-NL63 infection: comparison with rhinovirus-A1B
GEO Series GSE254967. Mus musculus. 18 samples. Type: Expression profiling by high throughput sequencing.
Comparison of gene expression in murine FoxP3+ T regulatory cells isolated from TNBC claudin-low model (T11) treated with anti-PD-1 with untreated tumors
GEO Series GSE182778. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Expression profile comparison of enriched bone marrow-derived tumor associated macrophages, tumor-associated alveolar macrophages, CD4 T cells, and total tumor-derived cells in lung cancer models with
GEO Series GSE169194. Mus musculus. 38 samples. Type: Expression profiling by high throughput sequencing.
Comparison between syngeneic kidney transplant and a model of allogeneic kidney transplant tolerance induced by anti-classII regimen in the rat
GEO Series GSE28474. Rattus norvegicus. 6 samples. Type: Expression profiling by array.
COORDE: A model comparison of resolved and parametrized orographic drag
<p>This data is used in the publication 'COnstraining ORographic Drag Effects (COORDE): a model comparison of resolved and parametrized orographic drag', under review in JAMES AGU.</p>
Data and R-Code from: How to account for behavioral states in step-selection analysis: a model comparison
<p>This repository provides the R-code and data used for the simulation and case study of the research paper: "How to account for behavioral states in step-selection analysis: a model comparison".</p><p>The folder "<strong>Pohle_et_al_2023_BehavioralStates_iSSA_Data</strong>" contains the landscape rasters used for data generation in the simulation study, and the bank vole (<i>Myodes glareolus</i>) movement data used in the case study on bank vole interactions:</p><ul><li>landscape10.RData and landscape50.RData: Landscape rasters for the simulation study.</li><li>Vole_case_control.rds: Case-control bank vole data for the case study.</li><li>Info_replicates.rds: Information about bank vole indiviuals and corresponding replicates for the case study.</li><li>Codebook_case_study.xlsx: Codebook for the case study data sets.</li><li>Read_me.txt</li></ul><p>The folder "<strong>Pohle_et_al_2023_BehavioralStates_iSSA_RCode</strong>" contains the R-scripts for the simulation and case study:</p><ul><li>Functions.R: Functions to apply HMMs, TS-iSSAs, and HMM-iSSAs to movement data; used for the simulation and case study.</li><li>Simulation_study.R: R-Code to run the simulation study. Parallel computation is used.</li><li>Results_simulation_study.R: R-Code to create the result figures and tables for the simulation study.</li><li>Case_study.R: R-Code to run the bank vole interaction case study. Parallel computation is used.</li><li>Results_case_study.R: R-Code to create the result figures and tables for the case study.</li><li>Read_me.txt</li></ul><p>Besides the simulation and case study from the paper, the included functions (<i>Functions.R</i>) can generally be used to perform an HMM-iSSA analysis.</p><p>For the bank vole movement data without control locations, see: Schlägel, U.E. et al. (2019). Data from: Estimating interactions between individuals from concurrent animal movements [Dataset]. Dryad. <a href="https://doi.org/10.5061/dryad.rt535m8">https://doi.org/10.5061/dryad.rt535m8</a>.</p><p><strong>Acknowledgements</strong></p><p>We thank Sophie Eden, Angela Puschmann and Pauline Lange for help with the bank vole data collection and maintenance of the outdoor enclosures.</p><p> </p><p> </p>
A comparison of model-based and model-free agents in solving semi-automatically generated PPDDL problems - Agent classification table
<p>This table classifies the agents used in the work to those which use models in their decision-making, which are model-based (MB), and those which do not, which are model-free (MF).</p>
The detailed results of model comparison between basline models and pepMTL in RT, CCS, MS/MS prediction
<p>This is a record file of the running results of the pepMTL model in the article "pepMTL: a synchronous multi-properties predictor for peptides enabled by multi-task framework and pre-trained protein language model", as well as the various benchmark models in RT, CCS, and MS/MS aspects. By carefully tiling the results of the run and saving the tiling results in the xlsx file.</p> <p>这是文章 "pepMTL: a synchronous multi-properties predictor for peptides enabled by multi-task framework and pre-trained protein language model"中pepMTL模型以及RT、CCS、MS/MS方面各个基准模型的运行结果的记录文件。通过对运行结果进行仔细整理,并将整理的结果保存在了xlsx文件中。</p> <p> </p>
JAMES technical report, scripts and data for "'Comparison of C3 photosynthetic responses to light and CO2 predicted by the leaf photosynthesis models of Farquhar et al. (1980) and Goudriaan et al. (1985)"
<p>Dear reader,</p> <p>In this repository you will find 7 MATLAB scripts and 3 Excel datasets. The script "A_curves_Figure2.m" calls the function scripts "FvCB_model_Figure2.m", "FvCB_model_Figure2_noTPU" and "G85_model_Figure2" to create Figure 2 of the JAMES publication. The script "G85_Rd_FigureS1" calls the function script "G85_model_FigureS1" to create Figure S1 of the Supporting Information. The script "r2_RMSE_Table2" calculates statistics displayed in Table 2 of the JAMES publication. The Excel worksheet "Table2.xlsx" contains the values in Table 2 of the JAMES publication for quick data copying. The Excel worksheets "FvCBparameters_fitted_withTPU.xlsx" and "FvCBparameters_fitted_noTPU.xlsx" contains fitted FvCB model parameter values that were obtained using the "fitaci" function from the plantecophys R package (Duursma, 2015). <br> <br> Kind regards,</p> <p>Kevin van Diepen </p>
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.