Systems biology, the study of the interactions and behaviour of the components of biological entities, including molecules, cells, organs, and organisms.
Systems biology has been responsible for some of the most important developments in the science of human health and environmental sustainability. It is a holistic approach to deciphering the complexity of biological systems that starts from the understanding that the networks that form the whole of living organisms are more than the sum of their parts. It is collaborative, integrating many scientific disciplines – biology, computer science, engineering, bioinformatics, physics and others – to predict how these systems change over time and under varying conditions, and to develop solutions to the world’s most pressing health and environmental issues.
Biological organisms are very complex, and their many parts interact in numerous ways. Thus, they can be considered generally as integrated systems. However, whereas an integrated complex system such as that of a modern airliner can be understood from its engineering design and detailed plans, attempting to understand the integrated system that is a biological organism is far more difficult, primarily because the number and strengths of interactions in the system are great and they must all be inferred after the fact from the system’s behaviour. In the same manner, the blueprint for its design must be inferred from its genetic material. That “integrated systems” point of view and all the associated approaches for the investigation of biological cells and organisms are collectively called systems biology.
Biological systems are enormously complex, organised across several levels of hierarchy. At the core of this organisation is the genome that contains information in a digital form to make thousands of different molecules and drive various biological processes. This genomic view of biology has been primarily ushered in by the human genome project. The development of sequencing and other high-throughput technologies that generate vast amounts of biological data has fuelled the development of new ways of hypothesis-driven research. Development of computational techniques for analysis of the large data, as well as for the modelling and simulation of the complex biological systems have followed as a logical consequence. Simulatable computational models of biological systems and processes form the cornerstone of the emerging science of systems biology.