Kim Branson

This paper shows that deep learning models for predicting biomarkers from histology images are confounded by interdependencies among biomarkers, leading to less accurate and less reliable predictions.

KGWAS improves GWAS power in small cohorts by integrating a functional knowledge graph, discovering more associations for rare diseases.

This paper introduces seq2cells, a model predicting single-cell gene expression from DNA sequence, revealing cell-type-specific variant effects and heterogeneity.

This paper introduces MoCoP, a contrastive pretraining framework that combines molecular graphs and cellular morphologies to improve QSAR model performance.

This paper compares quantum computing and genetic algorithms for codon optimization, finding quantum computers competitive and potentially superior in future generations.