David Brückner

Very excited for this meeting!

We have extended the abstract deadline by a week! Looking forward to seeing you many of you here!

This is a fantastic #biophysics job opportunity to join us in Dresden @mpipks.bsky.social! Apply by the 3rd of April!

Tissue phase transitions in development: more than just mechanics Summary: Tissue material phase transitions are classically thought to regulate tissue deformability. This Review emphasises their unexpected roles in directly influencing growth and patterning signall...

Excited to share our new review in @dev-journal.bsky.social on tissue phase transitions during development!

@karengrace12.bsky.social @nicolettapetridou.bsky.social

🔗 doi.org/10.1242/dev....

We summarised the many roles of material phase transitions in development (and they are not just mechanical 🤔)

Amazing and so well deserved! 🥳🥳

I’m thrilled to share that I will join @gustaveroussy.fr as a Group Leader!

Our objective: to understand how mechanochemical feedbacks regulate tumor dynamics and plasticity, with the overarching goal of bridging tissue mechanobiology and tumor pathophysiology using human organoids.

Best possible lab for a PhD / postdoc! Stay tuned for future openings and wonderful science.

From models to molecules: self-organized and instructed modes of developmental patterning www.nature.com/articles/s41... - nice piece by @davidbrueckner.bsky.social

Endogenous FGFs drive ERK-dependent cell fate patterning in 2D human gastruloids Summary: In a 2D gastruloid model for human gastrulation, FGF4 and FGF17 signal through basolateral receptors to induce primitive streak-like cells and derivatives, potentially restricted by FGF8.

After being reviewed as a preprint in Elife our paper about endogenous FGF signaling in 2D human gastruloids is now published in Development:
journals.biologists.com/dev/article-...

Anti-resonance in developmental signaling regulates cell fate decisions Human cells decode dynamics Wnt signals using an anti-resonant filter that suppresses intermediate-frequency inputs and is capable of redirecting developmental fate outcomes, including germ-layer spec...

In a really fun collaboration with Max Wilson’s lab at UCSB, we’ve developed a simple model that can capture the non-monotonic expression of Wnt target genes with respect to frequency in periodic (optogenetic) Wnt pulses: elifesciences.org/articles/107.... Great work Sam, Olivier, Naomi and Ryan :)

New preprint! We show how mesoscopic nonequilibrium fluctuations in active gels emerge from the breaking of detailed balance at the molecular scale. Warning: Long technical paper ahead! Enjoy! @mpipks.bsky.social @ub.edu @ubics.bsky.social @icreacommunity.bsky.social

arxiv.org/abs/2601.20483

Our latest: A gene selection method for single-cell RNA-seq that identifies developmental & spatial patterns missed by other analysis pipelines

ESFS: A Noise-Resilient Framework for Feature Selection and Marker Gene Discovery in Single-Cell Transcriptomics | bioRxiv www.biorxiv.org/content/10.6...

Our review on Marr's levels in embryonic development is now out in @prxlife.bsky.social !

journals.aps.org/prxlife/abst...

Visiting @hhmijanelia.bsky.social just before the winter storm hits! So much awesome science here!

Prof. Fiona Doetsch has been awarded the 2026 Louis-Jeantet Prize for Medicine!
Her discoveries reveal how neural stem cells support lifelong brain plasticity and repair. 🧠
Read more: www.biozentrum.unibas.ch/news/detail/...

Welcome to Basel @robinjournot.bsky.social !! :)

My time at @institutcurie.bsky.social is done! Over the past months, I completed my PhD, published my first first-author paper in DevCell (www.cell.com/developmenta..., and submitted my first last-author manuscript to bioRxiv (www.biorxiv.org/content/10.1...).

Feb 1 deadline approaching for our @kitp-ucsb.bsky.social QBio summer course on Physical Principles of Morphogenesis in Plants and Animals. @streichan.bsky.social
@maurazimmermann.bsky.social @maizel-lab.org @yusuke-mori.bsky.social @akankshi.bsky.social @nicolettapetridou.bsky.social

Biophysics of organoids In this review, Weichselberger, Moore et al. discuss how physics-based approaches illuminate organoid development and homeostasis by integrating mechanical, chemical, and informational processes. They...

Interested in the biophysics of organoids? We just published a review in Dev Cell—take a look! dlvr.it/TPyTb8 #Organoids #Biophysics

Self-organized or instructed?

My @natrevgenet.nature.com Journal Club traces how classic papers revealed two modes of developmental patterning & why the debate between Turing and Wolpert is as timely as ever for organoid engineering today

www.nature.com/articles/s41...

And here is the PDF of the 4th course @college-de-france.fr. You will find the justification and presentation of geometric representation of cell decisions, a parsimonious mathematical model for signalling and cell state transitions

tinyurl.com/yc7u296j

Here is the link to download the PDF of my course#5 on Biological computation. I present & discuss Self-tuning, Adaptation and Learning in biological (non-neuronal) systems, in particular during embryonic development.
This course contains various personal ideas/proposals.
tinyurl.com/hcpwsbtm

Qu’est-ce que l’information biologique (suite) ? (5) - Thomas Lecuit (2025-2026) Enseignement 2025-2026 : Qu’est-ce que l’information biologique (suite) ? Cours du 18 décembre 2025 : Apprentissage non neuronal dans un système vivant Professeur : Thomas Lecuit Chaire Dynamiques du vivant Retrouvez les enregistrements audios et vidéos du cycle : https://www.college-de-france.fr/fr/agenda/cours/qu-est-ce-que-information-biologique Tous les enseignements du Pr Thomas Lecuit : https://www.college-de-france.fr/chaire/thomas-lecuit-dynamiques-du-vivant-chaire-statutaire https://www.youtube.com/playlist?list=PLOj9pZ2YNGZ84uMY6DhPnqpL1rq5qNAVJ Le Collège de France est une institution de recherche fondamentale dans tous les domaines de la connaissance et un lieu de diffusion du « savoir en train de se faire » ouvert à tous. Les cours, séminaires, colloques sont enregistrés puis mis à disposition du public sur le site internet du Collège de France. Découvrez toutes les ressources du Collège de France : https://www.college-de-france.fr Soutenir le Collège de France : https://www.fondation-cdf.fr/faire-un-don Suivez-nous sur : Threads : https://www.threads.net/@collegedefrance Bluesky : https://bsky.app/profile/college-de-france.fr Facebook : https://www.facebook.com/College.de.France Instagram : https://www.instagram.com/collegedefrance LinkedIn : https://fr.linkedin.com/company/coll%C3%A8gedefrance

Please find below the link to watch the VIDEO of my course#5 @college-de-france.fr on Biological computation. I present and discuss Self-tuning, Adaptation and Learning in biological (non/neuronal) systems, in particular during embryonic development.
Enjoy!

tinyurl.com/4pv95an9

Super nice to see this awesome set of lectures online! A really timely perspective on biology through the lens of information, which inspires much of our own research as well.

Munro, E., Nance, J., & Priess, J. R. (2004). Cortical flows powered by asymmetrical contraction transport PAR proteins to establish and maintain anterior-posterior polarity in the early C. elegans embryo. Developmental cell, #EpithelialMechanics www.sciencedirect.com/science/arti...

This was a fun theory collaboration led by amazing postdoc Alex Zhang, in collab with Gasper Tkacik (ISTA)

Marr's three levels for embryonic development: information, dynamical systems, gene networks Developmental patterning comprises processes that range from purely instructed, where external signals specify cell fates, to fully self-organized, where spatial patterns emerge autonomously through…

Throughout this work, we found it really helpful to organize our thinking along 'Marr's three levels of analysis':
1. the computational problem
2. the algorithmic solution
3. biophysical implementation

Check out our review laying out this conceptual framework here: buff.ly/NE4JEOA

Remarkably, these optimal algorithms predicted by our theory are almost perfectly matched by minimalistic mechanistic models, including averaging through short-range diffusion and divisive normalization through a fast diffusing 'normalizer' species

Spatially uncorrelated noise: it's best to spatially average the input you get from the neighbors

Long-range correlated noise: it's best to perform a divisive normalization - normalize your measured value by that of your neighbors

Complex things happen in between these limits...