What is Systems Biology?

Systems biology is a rapidly evolving discipline that seeks to determine how complex biological systems function by integrating experimentally derived information through mathematical and computing solutions.

Today’s life sciences are driven by interdisciplinary research approaches integrating experimental molecular biology, clinical research, bioinformatics, computational biology, mathematics, computer science, physics, chemistry and biological engineering aiming to provide a better understanding of how biological systems respond to environmental cues and how they work in physiological and pathophysiological situations. This is systems biology. It represents a shift of emphasis, from the more classical reductionist view which focuses on identifying and characterizing the individual components, to a more holistic approach which focuses on the interactions between these components. “Components” can be at many different scales – for example the many proteins in a signal transduction pathway, the genes in a gene regulatory network, the cells in a tissue, or the neurons in a nervous system. In all cases the whole is greater than the sum of the parts.

Key features of systems biology include:

• Seeking to understand the emergent behaviour of systems – in other words how the interactions of multiple components can produce behavior that is impossible to predict from understanding the components individually. This unpredictability comes largely from the non-linearities of interactions between the components
• The interplay between theory and experiment – computational modeling is required due to the non-intuitive behaviour of complex systems, but in the field of systems biology modelling is constrained by real data. Similarly, experiments are guided by computational predictions, such that progress is made by iterative cycles between the two
• Highly interdisciplinary nature – the interplay mentioned above between theory and experiment, means that the field being characterized by the interaction of experimentalists with mathematicians, physicists and technologists

 

Systems biology is increasingly able to provide novel insights into complex biological networks, by computing these interactions and their kinetics and by generating in silico predictive models of cells, tissues and organs. The expectations are that systems biology will pave the way to the identification of novel disease genes, to the selection of successful drug candidates and finally to a more successful discovery of novel therapeutics.

Systems biology is a new way of studying biology, demanding new intellectual and organizational structures to deliver its full potential, requiring combined implementation of computational and experimental approaches, which is novel for most molecular biological sciences. This integration can only be achieved through a certain critical mass of experimentation, such as in genomics, proteomics, metabolomics, imaging etc. and with the help of mathematical analyses, modelling, informatics and statistics. Biological networks, both intracellular and in-and-between whole cells, tissues and organisms, connect thousands of molecular and higher-order functions, such that functioning of any part of the network depends on different, remote parts.