Markov is now part of C5R. See what we've been up to here.
I'll be traveling a bit this fall meeting scientists. Come grab a beer if you're in the area:
- Palo Alto — Tuesday, Sep 29 (Partiful link)
- Boston — Thursday, Oct 1 (Partiful link)
- Chicago — Friday, Oct 2 (Partiful link)
- LA — TBD
I'll be traveling a bit this fall meeting scientists. Come grab a beer if you're in the area:
- Palo Alto — Tuesday, Sep 29 (Partiful link)
- Boston — Thursday, Oct 1 (Partiful link)
- Chicago — Friday, Oct 2 (Partiful link)
- LA — TBD
Paper: Generative ranking enables scalable pretraining on noisy biological multisets
We built a world model of the cell—a single self-supervised model, trained on rankings of mRNA counts, that encodes:
- Where proteins sit in the cell — from nucleus to membrane to secreted
- Which proteins physically interact — direct substrates, scaffolds, complex partners
- How receptors signal — multi-hop kinase cascades recovered zero-shot
- Whether a target is druggable — and by which modality
- What transcription factors bind — including the sign of regulation and complex composition
State-of-the-art perturbation prediction. Monotonic scaling. No injected knowledge. No task-specific pretraining.
The model learned the cell because the cell is what generates the data. The right objective was all that was missing.
GCTCAGAAGCGCCGAGAGCGCGGCCGGGACGGTTGGAGAAGAAGGCGGCTCCCGGAAGGGGGAGAGACAAACTGCCGTAACCTCTGCCGTTCAGGAACCCGGTTACTTATTTATTCGTTACCCTTTTTCTTCTTCCTCCCCCAAAAACCTTTTCCTTTTCCCTTCTTTTTTTTTCCTTTTTGGGAGCTGAAAAATTTCCGGTAAGGGAAAGAAGGGCTCCTTTCGCTCCTTATTTCCCCGCCTCCTTCCCTCCCCCACCTTCCCCTCCTCCGGCTTTTTCCTCCCAACTCGGGGAGGTCCTTCCCGGTGGCCGCCCTGACGAGGTCTGAGCACCTAGGCGGAGGCGGCGC
GCTCAGAAGCGCCGAGAGCGCGGCCGGGACGGTTGGAGAAGAAGGCGGCTCCCGGAAGGGGGAGAGACAAACTGCCGTAACCTCTGCCGTTCAGGAACCCGGTTACTTATTTATTCGTTACCCTTTTTCTTCTTCCTCCCCCAAAAACCTTTTCCTTTTCCCTTCTTTTTTTTTCCTTTTTGGGAGCTGAAAAATTTCCGGTAAGGGAAAGAAGGGCTCCTTTCGCTCCTTATTTCCCCGCCTCCTTCCCTCCCCCACCTTCCCCTCCTCCGGCTTTTTCCTCCCAACTCGGGGAGGTCCTTCCCGGTGGCCGCCCTGACGAGGTCTGAGCACCTAGGCGGAGGCGGCGC
TACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAACCGTAGACCAGATAGCATAGACATACCGTAGACCAATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGATAGCATAGACATACCGTAATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACA
TACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAACCGTAGACCAGATAGCATAGACATACCGTAGACCAATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGATAGCATAGACATACCGTAATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACA
TACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAACCGTAGACCAGATAGCATAGACATACCGTAGACCAATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGATAGCATAGACATACCGTAATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACA
TACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAACCGTAGACCAGATAGCATAGACATACCGTAGACCAATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGATAGCATAGACATACCGTAATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACATACCGTAGACCAGATAGCATAGACA
Essays
Through a Glass Darkly: Mechanistic Interpretability as the Bridge to End-to-End Biology
November 2024
Single-Cell Encoder Models: Toward a Statistical Physics of Emergent Agency
June 2023
Hyperbolic Science: Or, Playing Games with Growth
August 2022
A Future History of Biomedical Progress
August 2022