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UID:DSC-20186
DTSTART;TZID=Europe/Berlin:20231013T100000
SEQUENCE:1697261997
TRANSP:OPAQUE
DTEND;TZID=Europe/Berlin:20231013T110000
URL:https://www.dresden-science-calendar.de/calendar/de/detail/20186
LOCATION:MPI-CBG\, Pfotenhauerstraße 10801307 Dresden
SUMMARY:Royer: \"Zebrahub – Multimodal Zebrafish Developmental Atlas Reve
 als the State-Transition Dynamics of Late-Vertebrate Pluripotent Axial Pro
 genitors\"
CLASS:PUBLIC
DESCRIPTION:Speaker: Loïc Alain Royer\nInstitute of Speaker: Chan Zuckerbe
 rg Biohub\, San Francisco\nTopics:\n\n Location:\n  Name: MPI-CBG (MPI-CBG
  Auditorium (big half))\n  Street: Pfotenhauerstraße 108\n  City: 01307 D
 resden\n  Phone: +49 351 210-0\n  Fax: +49 351 210-2000\nDescription: Eluc
 idating the developmental processes of organisms requires a comprehensive 
 understanding of cellular lineages in the spatial\, temporal\, and molecul
 ar domains. In this study\, we introduce Zebrahub\, a dynamic atlas of zeb
 rafish embryonic development that integrates single-cell sequencing time c
 ourse data with lineage reconstructions facilitated by light-sheet microsc
 opy. This atlas offers high-resolution and in-depth molecular insights int
 o zebrafish development\, achieved through the sequencing of individual em
 bryos across ten developmental stages\, complemented by trajectory reconst
 ructions. Zebrahub also incorporates an interactive tool to navigate the c
 omplex cellular flows and lineages derived from light-sheet microscopy dat
 a\, enabling in-silico fate mapping experiments.  Finally\, to demonstrate
  the versatility of our multi-modal resource\, we utilize Zebrahub to prov
 ide fresh insights into the pluripotency of Neuro-Mesodermal Progenitors (
 NMPs). Our publicly accessible web-based platform\, Zebrahub\, is a founda
 tional resource for studying developmental processes at both transcription
 al and spatiotemporal levels\, providing researchers with an integrated ap
 proach to exploring and analyzing the complexities of cellular lineages du
 ring zebrafish embryogenesis. This work was made possible by the developme
 nt of a broad range of technologies developed by my team\, such as the nap
 ari viewer\, novel state-of-the-art fluorescence microscopes (DaXi)\, self
 -supervised learning for bioimaging (CytoSelf)\, fast and scalable image p
 rocessing for light-sheet time-lapse data (DEXP)\, high-accuracy cell trac
 king at scale in developing embryos (ultrack)\, fast\, robust\, and user-f
 riendly image denoising (Aydin)\, and more recently the use of large langu
 age models for accelerating the dissemination of bioimaging skills and met
 hods (Omega).
DTSTAMP:20260511T215310Z
CREATED:20231003T053731Z
LAST-MODIFIED:20231014T053957Z
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