Erich J. Baker

This study uses hierarchical similarity to identify genetic factors of Behcet's disease and related autoimmune diseases with genetic overlap.

This paper introduces NESS, a tool that improves gene-disease association discovery by leveraging multi-species functional genomics data and network analysis to overcome data sparsity and bias.

The paper identifies host-microbiome interactions using systems genetics in mice, revealing mechanisms of microbial involvement in disease.

The paper integrates heterogeneous functional genomics data across species to identify genes and pathways underlying aging, finding Cd63 as a key gene with lifespan-extending effects in C. elegans.

This study introduces a modified N-Gram and Skip-Gram model for protein classification from primary sequence data, showing improved accuracy over existing methods.