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

doi:doi:10.48606/50

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

Abstract: This 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.

BibTex:

@dataset{Toulany_Nikan_2023,
    abstract = {Abstract: This 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.},
    author = {Toulany, Nikan},
    doi = {10.48606/50},
    institution = {RADAR},
    keyword = {'Twin Network', 'TwinNet', 'computational biology', 'deep learning', 'developmental biology', 'embryogenesis', 'high-throughput', 'machine learning', 'zebrafish'},
    title = {Datasets for "uncovering developmental time and tempo using deep learning"},
    url = {https://service.tib.eu/ldmservice/vdataset/rdr-doi-10-48606-50},
    year = {2023}
}