dc.contributor.author | Tahk, Maris-Johanna | |
dc.contributor.author | Torp, Jane | |
dc.contributor.author | Ali, Mohammed A.S. | |
dc.contributor.author | Fishman, Dmytro | |
dc.contributor.author | Parts, Leopold | |
dc.contributor.author | Grätz, Lukas | |
dc.contributor.author | Müller, Christoph | |
dc.contributor.author | Keller, Max | |
dc.contributor.author | Veikšina, Santa | |
dc.contributor.author | Laasfeld, Tõnis | |
dc.contributor.author | Rinken, Ago | |
dc.date.accessioned | 2022-01-19T09:53:52Z | |
dc.date.available | 2022-01-19T09:53:52Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | https://datadoi.ee/handle/33/432 | |
dc.identifier.uri | https://doi.org/10.23673/re-306 | |
dc.description.abstract | The "UT-GPCR001 microscopy of ligand binding to M4 muscarinic receptor in live CHO-K1-hM4 cells" dataset contains the raw microscopy images of the experiments along with images processed using the random forest algorithm and U-Net3 based deep convolutional neural networks for cell segmentation from bright-field images. The dataset contains experiments with a fluorescence ligand UR-CG072 and multiple M4 muscarinic receptor ligands. The dataset contains binding kinetic, fluorescence ligand saturattion and competition type experiments. | en |
dc.format | TIFF | |
dc.language.iso | en | |
dc.publisher | University of Tartu, Institute of Chemistry, Chair of Bioorganic chemistry | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | bright-field microscopy | |
dc.subject | fluorescence microscopy | |
dc.subject | GPCR | |
dc.subject | M4 muscarinic receptor | |
dc.subject | CHO-K1 | |
dc.subject | UR-CG072 | |
dc.subject | deep convolutional neural networks | |
dc.title | UT-GPCR001 microscopy of ligand binding to M4 muscarinic receptor in live CHO-K1-hM4 cells | en |
dc.type | info:eu-repo/semantics/dataset | |