Deciphering cell signaling networks with massively multiplexed biosensor barcodingGenetically encoded barcodes that uniquely identify cells expressing a particular fluorescent biosensor enable the simultaneous use of a broader set of biosensors in mixed cell populations and dynamic imaging of many cellular responses in a single experiment to reduce inter-experimental variability when interrogating complex biological interactions, such as the downstream consequences of receptor tyrosine kinase activation, with the help of image-based deep learning models for automated barcode unmixing.Genetically encoded barcodes that uniquely identify cells expressing a particular fluorescent biosensor enable the simultaneous use of a broader set of biosensors in mixed cell populations and dynamic imaging of many cellular responses in a single experiment to reduce inter-experimental variability when interrogating complex biological interactions, such as the downstream consequences of receptor tyrosine kinase activation, with the help of image-based deep learning models for automated barcode unmixing.Jr-Ming Yang, Wei-Yu Chi, Jessica Liang, Saki Takayanagi, Pablo A. Iglesias, Chuan-Hsiang Huanghttps://secure.jbs.elsevierhealth.com/action/getSharedSiteSession?redirect=https%3A%2F%2Fwww.cell.com%2Fcell%2Ffulltext%2FS0092-8674%2821%2901320-9%3Frss%3Dyes&rc=0http://www.cell.com/cell/inpress.rssCellCell RSS feed.Wireless News CampaignNovember 27, 2021

Powered by WPeMatico