Explore the science behind reproductive genetics, how Reticular reads embryo data, and the latest from our team.
From the team
Deep dives on the models, methods, and science behind Reticular.
An optimistic model of disease prevention, healthcare savings, and cheaper reproductive technology. Explore the assumptions in our interactive calculator.
Reticular Team
Exploratory analysis
GPN-Star expands rare-variant association signals beyond NeuroRisk, with modest internal prediction gains for selected traits.
Reticular Team
Research Team
Our latest technical whitepaper: modeled risk reductions, stronger genetic prediction, and validation within families.
Reticular Team
Research update
Reticular is scaling genomic AI for embryo screening, enabling better polygenic prediction for IVF families today on the path to curing heritable disease tomorrow.
John Yang
Co-Founder & CEO
Complex traits are substantially heritable, but today's best polygenic models explain only a fraction of that variance. We cover the landscape and what Reticular is building.
John Yang
Co-Founder & CEO
A look inside our paper on interpretable protein structure prediction using sparse autoencoders and what it means for trustworthy protein AI.
Reticular Team
Research Team
A case study showing how two neurons in a protein language model encode the catalytic machinery of serine protease.
Reticular Team
Research Team
Reticular launched on Y Combinator to share our work on embryo selection, clearer genetic risk reports, and more informed IVF decisions.
John Yang
Co-Founder & CEO