Leveraging evolution to engineer biology

We're testing an evolution-based drug discovery model
with an iterative loop of computational prediction
and experimental validation.

Target identification

Mining billions of years of evolution to systematize target discovery

We integrate across evolutionary scales to identify the causal bases of biological traits.

Model selection

Improving outcomes by picking useful research organisms

We're applying our platform to match disease biology with the most human relevant organisms.

Biologics design

Designing proteins from evolutionary principles

We develop statistical models to predict fitness and function. Our closed loop lets us experimentally test predictions and iterate on our models.

Technology development

Building assays and tools to test our predictions

We're developing and deploying organism-agnostic tools to investigate disease mechanisms.

Target identification

Mining billions of years of evolution to systematize target discovery

We integrate across evolutionary scales to identify the causal bases of biological traits.

Model selection

Improving outcomes by picking useful research organisms

We're applying our platform to match disease biology with the most human relevant organisms.

Biologics design

Designing proteins from evolutionary principles

We develop statistical models to predict fitness and function. Our closed loop lets us experimentally test predictions and iterate on our models.

Technology development

Building assays and tools to test our predictions

We're developing and deploying organism-agnostic tools to investigate disease mechanisms.

We publish our work and release open-source tools and resources for the scientific community.

Use our tools

Check out our latest research

result30 Apr 2026

A benchmark for the next generation of genotype–phenotype mapping

Despite their limitations, linear methods dominate the field of G–P mapping. In this study, we assess the performance of common linear methods at phenotype and variant effect prediction as a benchmark for more sophisticated methods.

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result02 Apr 2026

Assembly and annotation artifacts can lead to problematic protein structural inferences

Protein structures inferred by protein structure prediction algorithms have incredible potential, but can contain errors stemming from incorrect input sequences. Here, we investigate one such case in which tandem-domain proteins appear to have been erroneously inferred.

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result28 Mar 2026

Spontaneous Raman spectroscopy detects chemical perturbation of protein structure

Using 785 nm spontaneous Raman benchmarked against size-exclusion chromatography, we detected disulfide bond reduction, metal chelation effects, and pH-induced changes in diverse proteins.

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