Datasets for "Uncovering developmental time and tempo using deep learning"

Kurzanzeige
dc.contributor.authorToulany, Nikan
dc.contributor.otherMorales-Navarrete, Hernán
dc.contributor.otherÜnalan, Murat
dc.contributor.otherMüller, Patrick
dc.date.accessioned2025-04-02T09:17:24Z
dc.date.available2025-04-02T09:17:24Z
dc.date.created2023-03-29T19:36:34.000Z
dc.date.issued2023
dc.description.abstractThis is the data repository for training and testing the Twin Network. The imaging data repositories are divided into several packages based on independent experiments. The data comprises bright-field time-lapse images of zebrafish embryos acquired in multiple batches within multi-well plates using an Acquifer Imaging Machine. Individual embryo segments were identified and extracted using a trained neural network for object detection. Within these experiment folders, data are organized by microscope position and embryo number.
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dc.rightsCreative Commons Attribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/legalcode
dc.subjectBiology
dc.subjectTwin Network
dc.subjectTwinNet
dc.subjectzebrafish
dc.subjectembryogenesis
dc.subjectdeep learning
dc.subjectmachine learning
dc.subjecthigh-throughput
dc.subjectdevelopmental biology
dc.subjectcomputational biology
dc.subject.ddc570
dc.titleDatasets for "Uncovering developmental time and tempo using deep learning"eng
dspace.entity.typeDataset
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kops.citation.iso690TOULANY,  Nikan, 2023. Datasets for "Uncovering developmental time and tempo using deep learning"deu
kops.citation.iso690TOULANY,  Nikan, 2023. Datasets for "Uncovering developmental time and tempo using deep learning"eng
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