In 1952, the British neurophysiologists and nobel prize winners Alan Lloyd Hodgkin and Andrew Fielding Huxley constructed a mathematical model of the nerve cell. In 1960, Denis Noble developed the first computer model of a beating heart. Around the year 2000, with the establishment of Institute of Systems Biology was established in Seattle, systems biology emerged as a movement in its own right, spurred on by the completion of various genome projects, the large increase in data from the omics (e.g. genomics and proteomics) and the accompanying advances in high-throughput experiments and bioinformatics. Since then, various research institutes dedicated to systems biology have been developed. As of summer 2006, due to a shortage of people in systems biology several doctoral training centres have been established in the UK for systems biology.
- There are two major and complementary foci in systems biology:
Quantitative Systems Biology - otherwise known as "systems biology measurement", it focuses on measuring and monitoring biological systems on the system level.
- Systems Biology Modeling - focuses on mapping, explaining and predicting systemic biological processes and events through the building of computational and visualization models.
Quantitative systems biology
This subfield is concerned with quantifying molecular reponses in a biological system to a given perturbation.
Some typical technology platforms are:
- glycomics for sugars
These technologies are still emerging and many face problems that the larger the quantity of data produced, the lower the quality. A wide variety of quantitative scientists (computational biologists, statisticians, mathematicians, computer scientists, engineers, and physicists) are working to improve the quality of these approaches and to create, refine, and retest the models to accurately reflect observations.
Systems biology modeling
Using knowledge from molecular biology, a systems biologist can causally model the biological system of interest and propose hypotheses that describe a system's behavior. These hypotheses can then tested, with the possibility of used as a basis for mathematically model the system. The difference between the two stages of modeling is that causal models have at most the potential to explain the effects of a biological perturbation, while mathematical models, in theory, have predictive power.