Amanda M. Williams

The paper evaluates variant effect predictions for ARSA gene variants, finding that a bootcamp-trained model outperformed others and that deep learning slightly improved performance over simpler methods.

The paper evaluates variant prioritization methods for rare disease diagnosis using data from the Rare Genomes Project, finding that top models identify causal variants in most solved families and uncover potential candidates in unsolved ones.

The paper evaluates splicing prediction methods on 56 clinically validated variants, finding some methods match or exceed SpliceAI's performance but highlighting ongoing challenges in accuracy.

The paper examines inter-individual variability in human alveolar macrophage responses to Mycobacterium tuberculosis by analyzing gene and protein expression over time.