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Systems Biology

Systems Biology aims at a comprehensive and integrative view of any unit of biological organisation through experiment and the use of computer models with both predictive and explanatory power. This approach is applicable to any level of biological organisation from an individual metabolic pathway or signal transduction cascade to a cell, tissue, organ, organism, population, or ecosystem. This breadth of applicability means that Systems Biology will come to permeate all branches of biology, just as molecular biology has done over the last fifty years. Systems Biology exploits concepts and techniques from engineering, computer science, and mathematics in order to understand the complexity of living systems. For all that, systems biologists must keep in mind that living systems are the products, not of design, but of evolution through natural selection.

There has been a revolution in biology in recent years due to the availability of complete genome sequences for an increasing number of organisms. This has not only provided inventories of the ‘working parts’ (protein and RNA molecules) of organisms, but has also stimulated the development of technologies that allow the more or less comprehensive analysis of gene transcripts, proteins, and metabolites in a given cell type under a given set of conditions. It is the availability of these comprehensive data sets that has given birth (some would say ‘re-birth’) to Systems Biology. However, Systems Biology is not so much concerned with inventories of parts but, rather, with how those parts interact to produce working units of biological organisation whose properties are much greater than the sum of their parts.

The complexity of biological systems is such that systems biologists need to represent them in formal models. These may be either logical models or mathematical models, but their size and complexity demands the use of computers to manipulate them. These models should not only explain how living systems work, but also make specific predictions that can be tested by experiments. Systems Biology then proceeds via a ‘virtuous cycle’ in which model predictions are tested by experiment, the model is refined or revised in the light of the experimental data, and new (hopefully, more accurate) predictions are made. Many different kinds of skills are required to pursue this approach successfully and this means that Systems Biology is quintessentially a trans-disciplinary activity.