Sai Duraisingham

TL;DR: A set of computational algorithms are presented which, by leveraging the collective power of metabolic pathways and networks, predict functional activity directly from spectral feature tables without a priori identification of metabolites.

TL;DR: A large-scale network integration of publicly available human blood transcriptomes and systems-scale databases in specific biological contexts revealed distinct transcriptional signatures of antibody responses to different classes of vaccines, which provided key insights into primary viral, protein recall and anti-polysaccharide responses.

TL;DR: These results identify shared vaccine-induced signatures across multiple seasons and in diverse populations and might help guide the development of next-generation vaccines that provide persistent immunity against influenza.

TL;DR: A multiscale, multifactorial response network (MMRN) of immunity in healthy young and older adults immunized with the live attenuated shingles vaccine Zostavax is constructed and reveals striking associations between orthogonal datasets, such as transcriptomic and metabolomics signatures, cell populations, and cytokine levels.

TL;DR: The rapidly progressing field of systems biology has been shown to be useful in predicting immunogenicity and offering insights into potential mechanisms of protection in young adults and the identification of specific defects may be used to target novel vaccination strategies that improve efficacy in elderly populations.