Accuracy and Scalability of Machine Learning Methods for Genotype-Phenotype Association Data
Kieran Collienne, Lilin Zhang, Nicholas Sumpter, Meagan Leask, Michael Witbrock, Alex Gavryushkin
This study compares machine learning methods for predicting phenotypes from genetic data, finding that transformers outperform others in simulations and match state-of-the-art models on real data.
bioRxiv · Feb 13, 2025 · PreprintBioinformatics