Burhanuddin Sabuwala

The paper integrates gene expression and B cell receptor data to capture complementary B cell information, revealing substructure supported by both transcriptional and receptor features.

The paper benchmarks computational models predicting B. pertussis booster vaccine responses using multi-omics data from three cohorts, identifying key predictors of immunity and establishing a community resource for systems vaccinology.

The paper analyzes the bistability characteristics of mutual inhibition, mutual activation, and self-activation motifs using ODE simulations and explores their utility in coordinated gene expression.

The paper uses network topology analysis to identify key links in epithelial-mesenchymal plasticity networks that could inhibit metastasis by reducing positive feedback loops.

The paper analyzes single-cell expression profiles of circulating tumor cells (CTCs) across cancers, identifies EMT-related patterns, and develops a classifier to recognize CTCs using PBMC transcriptomes.