Tal Einav

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 benchmarks 49 algorithms for predicting B. pertussis vaccination outcomes, finding that purpose-built models outperform literature-based ones due to better handling of nonlinearities and data preprocessing.

This study shows that pre-existing immunity in ferrets enhances vaccine-induced antibody responses, reducing the need for booster shots and broadening protection against homologous and heterologous influenza strains.

The paper profiles 8,269 IPTG-inducible promoters to model gene expression and identify optimal promoter architectures for predictable transcriptional control.