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575
datasets available to search
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Dataset results
575 results for “Modeling Codes”
Model-driven design of synthetic N-terminal coding sequences for fine-tuning gene expression in yeast and bacteria
GEO Series GSE186378. Bacillus subtilis; Saccharomyces cerevisiae. 4 samples. Type: Other.
Positional Interpretation of Cis-Regulatory Code and Nucleosome Organization with Deep Learning Models
GEO Series GSE313524. Saccharomyces cerevisiae. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Race-specific transcriptome and Long non-coding RNA of ADT-resistant African-American prostate cancer cell models.
GEO Series GSE115307. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Matlab Codes for the data-driven model
<p>Main function: f_data_driven_model</p> <p>For detail of the methodology, please see the paper entitled "A machine-learning-based modeling for water quality in coastal waters- taking dissolved oxygen and hypoxia in Chesapeake Bay as an example" by Yu et al. </p> <p>This is the first version. </p>
Chesapeake Bay Model, Multi-River and Coastal Ocean tracer, CODE, Input Files, Scripts
<p>These data supplement the article: Du, J. and J. Shen, Transport of riverine material from multiple rivers in the Chesapeake Bay: the important control from the estuarine circulation. under review at the Journal Of Geophysical Research: Biogeoscience</p> <p>contact: Jiabi Du, jiabi@vims.edu</p> <p>Below are descriptions of the data files included here:</p> <p>1. CODE.zip</p> <p>-EFDC code for Chesapeake Bay Model</p> <p>- both hydro model and tracer release model are included</p> <p>- hydro model is run separately for each year. The first year is used to spin up and not be used for further analysis. e.g, run 2000 start the mode run from 1999,1,1 and only hydrodynamics field in 2000 is saved. </p> <p>2. Model run input files.zip:</p> <p>-input files for model runs from 1984-2014</p> <p>3. Monthly mean tracer output [1985-2014]</p> <p>-netCDF format results for monthly mean tracer concentrations from different sources (Susquehanna, Potomac, Rappahannock, York, James Rivers, and Coastal Ocean)</p> <p>-grid information are also included</p> <p>4. Matlab Scripts For Plotting.zip:</p> <p>-Matlab scripts used to plot the horizontal map, the vertical profile for the along channel section, the vertical profile for cross-channel sections. The script enables users to define the period and section no to plot. </p> <p>5. tracer influx and outflux ratio at 9 cross-section.xls:</p> <p>-an excel file contains the bottom tracer influx ratio and surface tracer outflux ratio for different rivers at different sections. </p>
Model Code and Various Datasets for Evaluation
Open the record for dataset details and reuse information.
Code for a data-driven model
<p>The archived code is to illustrate the framework of the data-driven model proposed in the article "A machine-learning-based model for water quality in coastal waters, taking dissolved oxygen and hypoxia in Chesapeake Bay as an example" submitted to Water Resource Research. </p> <p>A sample run is added. </p> <p>Additional information can be found in the "ReadMe" file within the archived zip file. </p>
Asserting Functional Equivalence between C Code and SCADE Models in Code-to-Model Transformations
<p>Video presentation of the SAST@CBSoft'20 paper 'Asserting Functional Equivalence between C Code and SCADE Models in Code-to-Model Transformations'.</p>
Matlab code associated with publication "Mathematical model of the multi-amino acid multi-transporter system predicts uptake flux in CHO cells"
<p>Matlab code associated with publication "Mathematical model of the multi-amino acid multi-transporter system predicts uptake flux in CHO cells" </p> <p>Published version : Ashley Sreejan, Mugdha Gadgil, Chetan J. Gadgil, Mathematical model of the multi-amino acid multi-transporter system predicts uptake flux in CHO cells, Journal of Biotechnology, Volume 344, 2022, Pages 40-49, ISSN 0168-1656</p> <p>Published version available at https://doi.org/10.1016/j.jbiotec.2021.12.003</p> <p>One version of the manuscript is available at doi:10.1101/2021.04.26.441392</p>
Data and Code for: Evaluation of the SPARTACUS-Urban Radiation Model for Vertically Resolved Shortwave Radiation in Urban Areas
<p>This contains the model outputs and analysis code for the article: Evaluation of the SPARTACUS-Urban Radiation Model for Vertically Resolved Shortwave Radiation in Urban Areas, Stretton et al. 2022, Boundary Layer Meteorology, 10.1007/s10546-022-00706-9</p>
Automating Code Review Activities 2.0 (datasets and models)
<p>Resources related by the research work <em>"Automating Code Review Activities 2.0".</em></p> <ul> <li><strong>dataset.zip </strong>contains all the preprocessed datasets used in our work;</li> <li><strong>models.zip</strong> contains the (best) checkpoints of the fine-tuned T5 models;</li> <li><strong>tokenizer.zip</strong> contains the Sentencepiece model and vocabulary trained on our pre-training dataset;</li> <li><strong>automating_code_review.zip</strong> contains the material to successfully run our Colab notebooks.</li> </ul> <p>More information in the replication package of our work: <a href="https://github.com/CodeReviewAutomation/code_review_automation">code_review_autmoation</a></p>
River network characteristic parameters data and landscape evolution model code
<p>This archive comprises two files utilized in the research conducted by Meng et al. The first file contains the code (.m) for simulating geomorphic evolution, while the second file contains the data (total.xlsx) for three measurements. Specifically, the code enables the rapid iteration of steady-state terrain elevation data for various initial slopes (%) and net rainfall intensities (mm/year). The river networks vector data is generated by the hydrological analysis tool, based on the aforementioned elevation data. The river networks characteristic parameters data (total.xlsx) can be derived by calculating the vector data with ArcMap software. These parameters include drainage area increments along mainstreams, stream course irregularity, and tributary junction angles.</p>
Data and Code for: Characterising the vertical structure of buildings in cities for use in atmospheric models
<p>This contains the data, model outputs, and analysis code for the article: Characterising the vertical structure of buildings for atmospheric models, Stretton et al. 2023, Urban Climate, https://doi.org/10.1016/j.uclim.2023.101560</p>
Raw data and analysis code of Transfusion model
<p>Raw data and analysis code of the paper entitled Development and External Validation of a Model Based on Electronic Health Records to Predict Minor, or Moderate, and Major Transfusion During On-pump Cardiac Surgery</p>
Raw data and analysis code of Transfusion model
<p>Raw data and analysis code of the paper entitled Development and External Validation of a Model Based on Electronic Health Records to Predict Minor, or Moderate, and Major Transfusion During On-pump Cardiac Surgery</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.