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Publication Year: 2022

501 to 510 of 523 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
UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth Jan 16, 2022 - Keemia instituudi andmed Tahk, Maris-Johanna; Torp, Jane; Ali, Mohammed A.S.; Fishman, Dmytro; Parts, Leopold; Grätz, Lukas; Müller, Christoph; Keller, Max; Veiksina, Santa; Laasfeld, Tõnis; Rinken, Ago, 2022, "UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth", https://doi.org/10.23673/RE-305, DATADOI, V1 The "UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth" dataset contains the raw microscopy images, corresponding bright-field Z-stack based contrast-enhanced images and the corresponding manual ground truth for fluorescence and bright-field images as well as ground truth generated from...
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
UT-GPCR003 Fluorescence anisotropy and microscopy measurements experimental metadata of ligand binding to M4 muscarinic receptors Jan 14, 2022 - Keemia instituudi andmed Tahk, Maris-Johanna; Torp, Jane; Ali, Mohammed A.S.; Fishman, Dmytro; Parts, Leopold; Grätz, Lukas; Müller, Christoph; Keller, Max; Veiksina, Santa; Laasfeld, Tõnis; Rinken, Ago, 2022, "UT-GPCR003 Fluorescence anisotropy and microscopy measurements experimental metadata of ligand binding to M4 muscarinic receptors", https://doi.org/10.23673/RE-303, DATADOI, V1 The "UT-GPCR003 Fluorescence anisotropy and microscopy measurements experimental metadata of ligand binding to M4 muscarinic receptors" dataset contains the raw fluorescence anisotropy data for ligand binding to M4 muscarinic receptors on budded baculovirus surface as well as processed data for fluorescence anisotropy measurements and microscopy me...

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

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

Jan 16, 2022 - Keemia instituudi andmed

Tahk, Maris-Johanna; Torp, Jane; Ali, Mohammed A.S.; Fishman, Dmytro; Parts, Leopold; Grätz, Lukas; Müller, Christoph; Keller, Max; Veiksina, Santa; Laasfeld, Tõnis; Rinken, Ago, 2022, "UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth", https://doi.org/10.23673/RE-305, DATADOI, V1

The "UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth" dataset contains the raw microscopy images, corresponding bright-field Z-stack based contrast-enhanced images and the corresponding manual ground truth for fluorescence and bright-field images as well as ground truth generated from...

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

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

Jan 14, 2022 - Keemia instituudi andmed

Tahk, Maris-Johanna; Torp, Jane; Ali, Mohammed A.S.; Fishman, Dmytro; Parts, Leopold; Grätz, Lukas; Müller, Christoph; Keller, Max; Veiksina, Santa; Laasfeld, Tõnis; Rinken, Ago, 2022, "UT-GPCR003 Fluorescence anisotropy and microscopy measurements experimental metadata of ligand binding to M4 muscarinic receptors", https://doi.org/10.23673/RE-303, DATADOI, V1

The "UT-GPCR003 Fluorescence anisotropy and microscopy measurements experimental metadata of ligand binding to M4 muscarinic receptors" dataset contains the raw fluorescence anisotropy data for ligand binding to M4 muscarinic receptors on budded baculovirus surface as well as processed data for fluorescence anisotropy measurements and microscopy me...

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