Systems biology is the study of the emergent properties of biological systems and its component parts using comprehensive and quantitative experimental methods that are interpreted by predictive mathematical and statistical models. Emergent properties result from “the whole being greater than the sum of its parts.” Systems biology melds high throughput experimentation with quantitative analysis and modeling to understand many critical biological processes.
The systems biology approach offers a comprehensive look at the interactions between pathogen and host. Embracing systems-biology practices helps us to reveal molecular and cellular networks that relay information and ultimately, design predictive, multi-scale models that guide us in understanding the complex interplay between a host and its pathogen. This knowledge, in turn, provides a foundation for rational drug and vaccine design.
In practice, we use high throughput genomics, proteomics, and other ‘omics technologies to comprehensively and quantitatively inventory the important components of pathogens and host immune responses. We then computationally and mathematically integrate different data types to extract and define the dynamic molecular networks that underlie the behavior. These networks are then modeled computationally to effectively generate hypotheses from a global perspective. In an iterative fashion this approach is used to predict outcomes for perturbations such as drugs, or for vaccine efficacy.