DATADOI

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DATADOI on multidistsiplinaarne avatud repositoorium teadusandmete jagamiseks ja avaldamiseks, mis põhineb avatud lähtekoodiga Dataverse tarkvaral.

Andmed tuleks talletada selle asutuse kollektsiooni, millega vähemalt üks kaasautoritest on seotud. DATADOI sisaldab praegu institutsionaalseid kollektsioone Tartu Ülikoolile, Tallinna Ülikoolile, Estonian Business Schoolile ja Eesti Teadusagentuurile.

Kui sobivat kollektsiooni veel ei ole, võtke ühendust DATADOI meeskonnaga aadressil datadoi@datadoi.ee.

DATADOI is a multidisciplinary open repository for sharing and publishing research data, based on the open-source Dataverse software.

Data should be deposited in the institutional collection assigned to the institution with which at least one of the contributors is affiliated. DATADOI currently includes institutional collections for the University of Tartu, Tallinn University, Estonian Business School, and the Estonian Research Council.

If a suitable collection does not yet exist, please contact the DATADOI team at datadoi@datadoi.ee.

Tartu Ülikool

Tallinna Ülikool

Estonian Business School

Eesti Teadusagentuur

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1,791 to 1,800 of 3,030 Results

RF-BF-2.zip Jan 16, 2022 - UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images Unknown - 1022.6 MB - MD5: aa0b7ff5cf8f238c870cd2ab01567ba5 Random forest based bright-field image cell segmentation model as Ilastik model
RF-FL-1.zip Jan 16, 2022 - UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images ZIP Archive - 154.0 MB - MD5: 909c653b0327db87759cd487debadda0 Random forest based fluorescence image cell segmentation model as Ilastik model
U-Net3-BF-1.zip Jan 16, 2022 - UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images ZIP Archive - 13.7 MB - MD5: 56fb5e9106cbfbb35df1a1ba7336825e U-Net3 based bright-field image cell segmentation model as Keras model
U-Net3-FL-1.zip Jan 16, 2022 - UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images ZIP Archive - 14.2 MB - MD5: 1a1aecbbb79cb68beeb6fbf9b6e0f011 U-Net3 based fluorescence image cell segmentation model as Keras model
Ilastik training.zip Jan 16, 2022 - UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth ZIP Archive - 514.9 MB - MD5: dfe14ab180619c2c1257079dd38de63c Images used for training Ilastik random forest models
migratsioonieelne_statistika.html Jan 16, 2022 - UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth HTML - 907 B - MD5: c07b6daef3dbee864bf87e6aa836cde2 2026. aasta migratsiooni käigus varasemast DataDOI süsteemist üle kantud kasutusstatistika kajastab tegevust eelmises DSpace-põhises süsteemis ega näita Dataverse’i uusi kasutusandmeid. Usage statistics carried over from the previous DataDOI system as part of the 2026 migration reflect activity in the former DSpace-based system and do not represent...
README.txt Jan 16, 2022 - UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth Plain Text - 5.7 KB - MD5: c8ed474cb7a894a97dda3ed9c0731318 README
U-Net3 training.zip Jan 16, 2022 - UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth ZIP Archive - 740.2 MB - MD5: 5ceb4b33824f9f4626018036e67019bc Images used for training U-Net3 based models
ASCII files.zip Jan 14, 2022 - UT-GPCR003 Fluorescence anisotropy and microscopy measurements experimental metadata of ligand binding to M4 muscarinic receptors ZIP Archive - 2.1 MB - MD5: 1dbffe547cd9e346dc7fb0ffb68a668f Raw fluorescence anisotropy experiment ASCII files generated by Gen5 software and measured with Synergy Neo plate reader
MIDAS files.zip Jan 14, 2022 - UT-GPCR003 Fluorescence anisotropy and microscopy measurements experimental metadata of ligand binding to M4 muscarinic receptors ZIP Archive - 15.4 MB - MD5: 617e80e5dbd4ab03c93d7f8ca909a412 MIDAS files in CSV or XLS format combining the measurement data and experimental metadata

RF-BF-2.zip

Jan 16, 2022 - UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images

Unknown - 1022.6 MB -

Random forest based bright-field image cell segmentation model as Ilastik model

RF-FL-1.zip

Jan 16, 2022 - UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images

ZIP Archive - 154.0 MB -

Random forest based fluorescence image cell segmentation model as Ilastik model

U-Net3-BF-1.zip

Jan 16, 2022 - UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images

ZIP Archive - 13.7 MB -

U-Net3 based bright-field image cell segmentation model as Keras model

U-Net3-FL-1.zip

Jan 16, 2022 - UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images

ZIP Archive - 14.2 MB -

U-Net3 based fluorescence image cell segmentation model as Keras model

Ilastik training.zip

Jan 16, 2022 - UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth

ZIP Archive - 514.9 MB -

Images used for training Ilastik random forest models

migratsioonieelne_statistika.html

Jan 16, 2022 - UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth

HTML - 907 B -

2026. aasta migratsiooni käigus varasemast DataDOI süsteemist üle kantud kasutusstatistika kajastab tegevust eelmises DSpace-põhises süsteemis ega näita Dataverse’i uusi kasutusandmeid. Usage statistics carried over from the previous DataDOI system as part of the 2026 migration reflect activity in the former DSpace-based system and do not represent...

README.txt

Jan 16, 2022 - UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth

Plain Text - 5.7 KB -

README

U-Net3 training.zip

Jan 16, 2022 - UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth

ZIP Archive - 740.2 MB -

Images used for training U-Net3 based models

ASCII files.zip

Jan 14, 2022 - UT-GPCR003 Fluorescence anisotropy and microscopy measurements experimental metadata of ligand binding to M4 muscarinic receptors

ZIP Archive - 2.1 MB -

Raw fluorescence anisotropy experiment ASCII files generated by Gen5 software and measured with Synergy Neo plate reader