Published on May 01, 2025 by Arcadia Science

Cross-trait learning with a canonical transformer tops custom attention in genotype–phenotype mapping

We added standard transformer components, omitted by Rijal et al. (2025) in their attention-based genotype–phenotype mapping. We found this addition substantially boosts predictive accuracy on their yeast dataset.

Cross-trait learning with a canonical transformer tops custom attention in genotype–phenotype mapping

The full pub is available here.

The source code to generate it is available in this GitHub repo (DOI: 10.5281/zenodo.15320438).

In the future, we hope to host notebook pubs directly on PubPub. Until that’s possible, we’ll create stubs like this with key metadata like the DOI, author roles, citation information, and an external link to the pub itself.


E
Evan Kiefl
Conceptualization, Formal Analysis, Investigation, Software, Validation, Writing
E
Erin McGeever
Conceptualization, Data Curation, Investigation, Software, Validation
R
Ryan York
Supervision