A quantitative-genetic decomposition of a neural network

From black box to glass box\: Making UMAP interpretable with exact feature contributions

A free, open-access library of high-quality organism illustrations for science communication

How do we balance labor and yield in high-throughput protein expression?

Efficient GFP variant design with a simple neural network ensemble

AutoOpenRaman\: Low-cost, automated Raman spectroscopy

Mapping the spectrum of archaeal protein sequence–structure relationships

Automating identification and quantification of mouse scratch behavior in video recordings

Lessons from our approach to bioprospecting in ticks

Assembling and annotating an Asgard archaea and giant virus dataset of over 840,000 proteins

G–P Atlas\: A neural network framework for mapping genotypes to many phenotypes

Modeling human monogenic diseases using the choanoflagellate *Salpingoeca rosetta*

Modeling human monogenic diseases using the tunicate *Ciona intestinalis*

A framework for modeling human monogenic diseases by deploying organism selection

Graph neural networks\: A unifying predictive model architecture for evolutionary applications

Phylogenies and biological foundation models

Epistasis and deep learning in quantitative genetics

*Chlamydomonas cpc1-1* mutant exhibits unexpected growth phenotypes