Näita lihtsat nimetuse kirjet

dc.contributor.authorTahk, Maris-Johanna
dc.contributor.authorTorp, Jane
dc.contributor.authorAli, Mohammed A.S.
dc.contributor.authorFishman, Dmytro
dc.contributor.authorParts, Leopold
dc.contributor.authorGrätz, Lukas
dc.contributor.authorMüller, Christoph
dc.contributor.authorKeller, Max
dc.contributor.authorVeikšina, Santa
dc.contributor.authorLaasfeld, Tõnis
dc.contributor.authorRinken, Ago
dc.date.accessioned2022-01-19T09:53:52Z
dc.date.available2022-01-19T09:53:52Z
dc.date.issued2022
dc.identifier.urihttps://datadoi.ee/handle/33/432
dc.identifier.urihttps://doi.org/10.23673/re-306
dc.description.abstractThe "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.formatTIFF
dc.language.isoen
dc.publisherUniversity of Tartu, Institute of Chemistry, Chair of Bioorganic chemistry
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectbright-field microscopy
dc.subjectfluorescence microscopy
dc.subjectGPCR
dc.subjectM4 muscarinic receptor
dc.subjectCHO-K1
dc.subjectUR-CG072
dc.subjectdeep convolutional neural networks
dc.titleUT-GPCR001 microscopy of ligand binding to M4 muscarinic receptor in live CHO-K1-hM4 cellsen
dc.typeinfo:eu-repo/semantics/dataset


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Näita lihtsat nimetuse kirjet

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