Matias Kaplan
a better world is possible
I am a synthetic biologist with a background in RNA devices, high-throughput biochemistry, structural biology and machine learning. I think industrial policy is neat and necessary.
As founding scientist at Atomic AI, I developed workflows for collecting large RNA structure datasets from high-throughput experiments to create state-of-the-art models for RNA structure prediction.
During my Bioengineering PhD in Christina Smolke's lab at Stanford I worked on understanding and developing new RNA-based small molecule devices for cell control.
As founding scientist at Atomic AI, I developed workflows for collecting large RNA structure datasets from high-throughput experiments to create state-of-the-art models for RNA structure prediction.
During my Bioengineering PhD in Christina Smolke's lab at Stanford I worked on understanding and developing new RNA-based small molecule devices for cell control.
Selected Publications
- ATOM‐1: A Foundation Model for RNA Structure and Function Built on Chemical Mapping Data bioRxiv, 2023
- Highly multiplexed selection of RNA aptamers against a small molecule library PLoS One, 2022
- Engineering synthetic RNA devices for cell control Nature Rev Genetics, 2022
- Structurally Mapping Antigenic Epitopes of Adeno‐Associated Virus 9: Development of Antibody Escape Variants Journal of Virology, 2022
- Massively parallel RNA device engineering in mammalian cells with RNA‐Seq Nature Comms, 2019
- Conformational control of DNA target cleavage by CRISPR‐Cas9 Nature, 2015
- Structures of Cas9 Endonucleases Reveal RNA‐Mediated Conformational Activation Science, 2014