The Thalion Initiative (US)

Evo 2, our fully open-source biological foundation model trained on trillions of DNA tokens spanning the entire tree of life, is out in @Nature today We & the scientific community have done a lot with this @arcinstitute @nvidia model in the last year! 🧵👇

Evo 2, our genome language model that generalizes: - across biological prediction and design tasks, - across all modalities of the central dogma, - across molecular to genome scale, and - across all domains of life, is published today in @Nature.

I'm delighted to share our curated list of 100 open problems in ageing science. This represents a collective, systematic effort to map the key challenges and knowledge gaps across biogerontology. 1/3 link.springer.com/article/10.100…

So excited to share my @TEDx talk on human longevity soon! Proud to have helped curate this wonderful event alongside @johnkwerner at the @MITMuseum, @WHOOP, and The Quin House. Got to pick some of my favorite people in aging bio (@mkaeberlein, @AlexJColville, @MartinBJensen, @MaxUnfried) to share a diverse set of views on what I believe will be one of the most impactful breakthroughs in human history. Truly cannot wait to share more soon :)

Final version is out: aging as the result of loss of goal-directedness advanced.onlinelibrary.wiley.com/doi/epdf/10.10… @BeneHartl @LPiolopez "Although substantial advancements are made in manipulating lifespan in model organisms, the fundamental mechanisms driving aging remain elusive. No comprehensive computational platform is capable of making predictions on aging in multicellular systems. Focus is placed on the processes that build and maintain complex target morphologies, and develop an insilico model of multiscale homeostatic morphogenesis using Neural Cellular Automata (NCAs) trained by neuroevolution. In the context of this model: 1) Aging emerges after developmental goals are completed, even without noise or programmed degeneration; 2) Cellular misdifferentiation, reduced competency, communication failures, and genetic damage all accelerate aging but are not its primary cause; 3) Aging correlates with increased active information storage and transfer entropy, while spatial entropy distinguishes two dynamics, structural loss and morphological noise accumulation; 4) Despite organ loss, spatial information persists in tissue, implementing a memory of lost structures, which can be reactivated for organ restoration through targeted regenerative information; and 5) rejuvenation is found to be most efficient when regenerative information includes differential patterns of affected cells and their neighboring tissue, highlighting strategies for rejuvenation. This model suggests a novel perspective on aging caused by loss of goal-directedness, with potentially significant implications for longevity research and regenerative medicine."