🎉 As the year winds down, we are filled with gratitude for an inspiring year of science, collaboration, and discovery. Wishing you all a joyful festive season and a bright, groundbreaking 2025 ahead! 🧬🔬🌟
A new preprint from the @Knoblich_lab and colleagues from @MaxPerutzLabs and @CeMM_News characterizes how different protocols and starting cell lines affect the variety of cell types in brain organoids. The team also proposes improved protocols for producing brain organoids.
All data is easily accessible in our Vienna brain organoid data explorer. You can look for your favorite gene or search for entire biological processes based on GO Terms. Check it out: https://t.co/X41LWB2juY
We also provide RNA-seq data for cell lines in all protocols across organoid development. We quantify sources of variability (1. organoid developmental stage, 2. protocol, 3. cell line) and provide early signatures consistent with protocol-driven organoid derivation.
Save the date for the Athens International Symposium on 3-4 April 2025! Join scientists as they share their latest research on neural stem cells. Registration & abstract submission will open in October 👉 https://t.co/RxcP5OG9RT
@VanderhaeghenP2 @studerl@BrunetLab@Knoblich_lab
New paper alert! The @Knoblich_Lab partnered with researchers at the @humantechnopole and @unimib to develop new brain organoids with distinct cortical areas and front-to-back patterning and study human-specific brain development and disorders. Read more: https://t.co/400ZaVys6U
Chong Li, postdoc at the #Knoblich_Lab, will soon leave IMBA to take a new position as group leader at the Chinese Institute for Brain Research (@chinese_brain). Learn more about Chong’s journey at IMBA and his future position here: https://t.co/jBJBaAMTbl
Extremely grateful for the support of the @Knoblich_lab and @IMBA_Vienna during this postdoc journey, where I met amazing scientists from around the world! Excited to start my own group soon at CIBR to continue exploring some of the most fascinating areas of human brain research!
Wohoo! Great work, @FahrenbergerM , on improving scRNA-seq analyses. Easy to use, implementation in Seurat workflow, better results across the board! Happy to have pitched in. Congratulations!
I m happy to present our latest preprint, and the main work of my PhD-project:
"GTestimate: Improving relative gene expression estimation in scRNA-seq using the Good-Turing estimator"
In this manuscript we introduce a new normalization method for scRNA-seq data.
We're at the cover of Cell Stem Cell.
We're at the cover of Cell Stem Cell.
We're a-
(I can barely believe it. 🤯)
We found out why some people are born without the main interhemispheric bridge. 🧠
👏 to @PhDexheimer for this beautiful illustration of the corpus callosum.