Systems biology

Systems biology is an approach to life science that studies living things as interacting networks rather than one gene or protein at a time. Its central idea is that many properties of a cell, organ or organism, such as a steady rhythm, a switch-like response or resistance to damage, emerge from the way the parts are connected and cannot be understood by studying each part alone.

Work in the field combines large-scale measurement with mathematics and computing. Researchers collect data on several levels at once, such as the genome, transcriptome, proteome and metabolome, often after deliberately disturbing the system with a drug, a mutation or a change in environment. They then build models, from network maps to sets of equations, that predict how the system should respond, test those predictions in new experiments and refine the models in a repeating cycle. The field is therefore highly interdisciplinary, bringing together biologists, engineers, physicists, computer scientists and mathematicians.

Examples include genome-scale metabolic models that predict which genes a bacterium needs to grow, models of the cell cycle and circadian clock, and network studies of disease that look for drug targets or explain why patients respond differently to treatment. Systems biology overlaps with bioinformatics, which supplies many of its data tools, and with synthetic biology, which uses similar models to design new circuits.