AlphaFold just stopped predicting lone proteins and started predicting the conversations between them. 1.7 million high-confidence protein complexes — open, searchable, downloadable — changes structural biology overnight.
Tufts and Wyss researchers engineered neurobots from Xenopus frog cells that spontaneously self-assemble functional neural networks—driving complex behavior, elongated morphology, and 6,774 upregulated genes. Biology just built its own control system.
Nine years after Florian Markowetz declared all biology computational biology, the field has inverted. We no longer crunch data about life. We program life itself as the ultimate computing substrate.
Cambridge engineers built a single-material robotic skin that detects 860,000 signal pathways at once. It's not just a sensor — it's the first serious step toward skin as a distributed biological computer.
OpenMed_AI just dropped every Psychiatric Genomics Consortium GWAS dataset — 1.14 billion rows, 52 studies, 12 disorders — on Hugging Face in clean Parquet format. The data-wrangling wall is gone. What gets built next?
DeepMind's AlphaGenome reads up to 1 megabase of raw DNA at single-base-pair resolution — finally mapping the regulatory dark matter that CRISPR needs to cure what proteins alone never could.
Gladstone Institutes and NVIDIA just released MaxToki — a temporal foundation model trained on nearly 1 trillion gene tokens from 175 million single cells across the human lifespan. It doesn't just describe aging. It predicts interventions that push cells back toward youthful identity. Yamanaka is on the paper.
Four USB-sized organ chips built from astronaut bone-marrow cells are flying on Artemis II — living biological computers designed to model, in real time, how the human body responds to deep-space radiation and microgravity.
Tufts researchers just handed VLA models a decisive defeat. Neuro-symbolic AI outperforms billion-parameter robot models while consuming 100× less energy — and the implications run deeper than robotics.