Kirk Smith

Decomposing polygenic risk of coronary artery disease into distinct biological processes

The paper decomposes polygenic risk of coronary artery disease into distinct biological processes using latent factor decomposition of genetic variants.

Recon8D: A metabolic regulome network from oct-omics and machine learning

The paper uses machine learning to predict metabolomic variation across cancer cell lines using 8 omic layers, identifying key predictors and signaling pathways.

Multi-ancestry Polygenic Mechanisms of Type 2 Diabetes Elucidate Disease Processes and Clinical Heterogeneity

This study identifies genetic subtypes of type 2 diabetes across diverse ancestries, revealing ancestry-specific risk profiles and BMI thresholds.

High-throughput Genetic Clustering of Type 2 Diabetes Loci Reveals Heterogeneous Mechanistic Pathways of Metabolic Disease

This paper clusters T2D genetic loci into ten groups using bNMF, identifying distinct biological mechanisms and clinical associations.

Metabolic signatures of regulation by phosphorylation and acetylation

The paper uses machine learning to classify metabolic regulation by phosphorylation and acetylation across multiple organisms and conditions.