Current Research
My work at Arcadia Science uses evolution to expand the scope, accuracy, and efficiency of biological research.
Current foci include defining how evolution determines what machines can learn, building nonlinear genotype–phenotype maps, and expanding the biomedical research organismal portfolio.
We’re deeply committed to open science at Arcadia. All of our work is published as living documents that we invite the community to review. The code and data needed to reproduce each publication are openly shared and well-documented. Read more about this publishing philosophy here.
2026
P Avasthi, R York, (2026). Biology needs to become prospective.
JR Golden, E Kiefl, R York. (2026). MSA-based pLMs encode evolutionary distance but don’t reliably exploit it.
2025
JR Golden, G Sandler, R York. (2025). A quantitative-genetic decomposition of a neural network
JR Golden, R York. (2025). From black box to glass box: Making UMAP interpretable with exact feature contributions.
JR Golden, G Sandler, R York. (2025). Equivalent linear mappings of deep networks are a promising path for biology.
BM Bigge, R Lane, E McGeever, H Wood, R York. (2025). Efficient GFP variant design with a simple neural network ensemble.
I Nocedal, R York. (2025). Do protein language models understand evolution? Mixed evidence from ancestral sequences and ESM2.
SA Goldstein, R York. (2025). Mapping the spectrum of archaeal protein sequence–structure relationships.
DG Mets, R York. (2025). G–P Atlas: A neural network framework for mapping genotypes to many phenotypes.
A Bell, A Patton, R York. (2025). Graph neural networks: A unifying predictive model architecture for evolutionary applications.
P Avasthi, A Bell, K Cheverall, S Chou, M Hochstrasser, A Stolfi, D Sun, R York. (2025). Modeling human monogenic diseases using the tunicate Ciona intestinalis.
P Avasthi, A Bell, K Cheverall, S Chou, M Hochstrasser, A Patton, D Sun, R York. (2025). A framework for modeling human monogenic diseases by deploying organism selection.
P Avasthi, A Bell, D Booth, K Cheverall, S Chou, M Hochstrasser, D Sun, R York. (2025). Modeling human monogenic diseases using the choanoflagellate Salpingoeca rosetta.
P Avasthi, A Bell, E McGeever , R York. (2025). Phylogenies and biological foundation models.
A Bell, K Cheveralls, G Sandler, R York. (2025). Epistasis and deep learning in quantitative genetics.
B Bigge, E Kiefl, E McGeever, G Sandler, R York. (2025). Cross-trait learning with a canonical transformer tops custom attention in genotype–phenotype mapping.
P Avashthi, B Bigge, M Hochstrasser, E Kiefl, R Roth, U Sabbagh, R York. (2025). Closing the divide between analysis and publication: The notebook pub.
A Bell, E McGeever, A Patton, G Sandler, R York. (2025). Predicting antimicrobial resistance phenotypes across 7,000 E. coli genomes.
A Bell, B Bigge, F Celebi, M Hochstrasser, A Radkov, R York. (2025). Structure-based protein clustering sometimes, but not always, provides insight into protein function.
A Bell, A Borges, F Celebi, S Chou, R Dutton, M Hochstrasser, E McDaniel, A Patton, T Reiter, E Weiss, R York. (2025). Comparative phylogenomic analysis of chelicerates points to gene families associated with long-term suppression of host detection.
2024
P Avasthi, A Bell, E McGeever, A Patton, R York. (2024). Leveraging evolution to identify novel organismal models of human biology
P Avasthi, A Bell, M Hochstrasser, R York. (2024). A data-driven approach to match organisms and research problems.
P Avasthi, R York. (2024). The known protein universe is phylogenetically biased.
A Bell, B Bigge, A Borges, S Chou, R Dutton, J Gehring, M Hochstrasser, E McDaniel, K Poskanzer, T Reiter, R York. (2024). Identification of capsid-like proteins in venomous and parasitic animals.
P Avasthi, A Bell, B Bigge, B Braverman, T Essock-Burns, M Hochstrasser, R Lane, C MacQuarrie, D Mets, A Patton, D Sun, H Wood, R York. (2024). Raman spectroscopy enables rapid and inexpensive exploration of biology.
P Avasthi, A Bell, B Bigge, M Hochstrasser, A Radkov, D Sun, H Wood, R York. (2024). How can we biochemically validate protein function predictions with the Ras GTPase family?.
P Avasthi, A Bell, B Bigge, M Hochstrasser, A Radkov, D Sun, H Wood, R York. (2024). How can we biochemically validate protein function predictions with the deoxycytidine kinase family?.
P Avasthi, A Bell, B Bigge, M Hochstrasser, A Radkov, D Sun, H Wood, R York. (2024). A strategy to validate protein function predictions in vitro.
A Bell, B Braverman, M Hochstrasser, C MacQuarrie, D Mets, T Reiter, R York. (2024). The phenotype-o-mat: A flexible tool for collecting visual phenotypes.
P Avasthi, A Bell, B Bigge, M Hochstrasser, I Kolb, D Mets, M Morin, A Patton, D Sun, T Reiter, R York. (2024). A structurally divergent actin conserved in fungi has no association with specific traits.
P Avasthi, B Bigge, F Celebi, M Hochstrasser, T Reiter, D Sun, R York. (2024). Exploring the actin family: A case study for ProteinCartography.
2023
P Avasthi, F Celebi, M Hochstrasser, D Mets, R York. (2023). Harnessing genotype-phenotype nonlinearity to accelerate biological prediction.
F Celebi, S Chou, J Eisen, M Hochstrasser, E McDaniel, E McGeever, A Patton, T Reiter, D Sun, R York. (2023). NovelTree: Highly parallelized phylogenomic inference.
F Celebi, M Hochstrasser, D Matus, D Mets, A Patton, T Reiter, R York. (2023). Applying information theory to genetics can better explain biological phenomena.
P Avasthi, B Bigge, B Braverman, F Celebi, T Essock-Burns, M Hochstrasser, G Garcia, C MacQuarrie, D Matus, D Mets, T Reiter, H Wood, R York. (2023). Phenotypic differences between interfertile Chlamydomonas species.
P Avasthi, F Celebi, M Hochstrasser, A Patton, R York. (2023). Raman spectra reflect complex phylogenetic relationships.
P Avasthi, F Celebi, T Essock-Burns, J Gehring, M Hochstrasser, D Matus, D Mets, R York. (2023). Gotta catch ‘em all: Agar microchambers for high-throughput single-cell live imaging.
2022
P Avasthi, F Celebi, M Hochstrasser, R York. (2022). Distinct spatiotemporal movement properties reveal sub-modalities in crawling cell types.