CSIRO’s image analysis aids the rapid screening of microscope images of cells.

Complexity in biological systems

From genes to populations, from individuals to ecosystems, CSIRO scientists are researching the richness of biological systems and exploring their capacity for adaptation and self-organising behaviour.

• 22 January 2008 | Updated 14 October 2011

• Modelling biological complexity in CSIRO
• What are complex biological systems and what is Complex Systems Science?
• Research projects

Modelling biological complexity in CSIRO

CSIRO takes an interdisciplinary approach to Complex Systems Science (CSS), sharing knowledge across projects so that techniques and approaches can be applied from one area to another.

With support from the CSIRO Centre for Complex Systems Science, scientists from various backgrounds are applying CSS approaches to understand complexity in:

• human biocomplexity
• animal biocomplexity
• plant biocomplexity.

Our scientists are developing and applying new analytical techniques in CSS to reshape our understanding and provide practical solutions.

What are complex biological systems and what is Complex Systems Science?

Biological systems are aggregates of many smaller interacting biological entities, ranging in scale from genes and cells through whole organisms such as plants, animals and humans to communities and populations.

Two properties set a complex system apart from one that is merely complicated:

• emergence
• self-organisation.

Emergence is the appearance of behaviour that could not be anticipated from a knowledge of the parts of the system alone.

The expression of a genetic characteristic in a single organism is an emergent property of the interactions between its genes and between the genes and their environment.

Fluctuations in the population of a species are an emergent feature of the interactions within the population and with what it eats (and is eaten by!)

Complicated artefacts like motor cars or power plants also have emergent features in this sense so a further property is needed to distinguish complex systems. This is self-organisation.

This means that there is no external controller or planner engineering the appearance of these emergent features. They appear spontaneously.

Further examples of complexity in biological systems include:

• immune system function
• brain function
• evolution.

The challenge of understanding and predicting complex system behaviour has risen in importance with the realisation that much of the unpredictable behaviour observed in real world situations is a function of the complex systems operating around us.

To improve our understanding of complex system behaviour, scientists have developed mathematical techniques based on computer models of these systems, to help think about them in new ways.

These models are revealing and explaining a range of emergent system behaviours and providing a deeper understanding of entire systems and their responses, with often surprising and unexpected results.

Complex systems analysis of gene expression is one of the newer areas of CSS research worldwide, and is taking place at the interface between biology, physics and mathematics.

Research projects

CSIRO is undertaking work on complexity in both animal and plant biological systems and in humans.

Some of our research projects in animal and plant complex systems include:

• complex systems analyses of invasive species and their management
• developing models to manage major disease outbreaks in cattle
• gene interaction networks
• nematode gut parasite species interaction dynamics in sheep
• pheromone plume tracking by insects
• interrelationships in complex ecosystems.

Some of our research projects in human biology include:

• using massive agent-based models to predict the spread of an avian flu pandemic
• the dynamics of complex networks in molecular, cellular and tissue biology
• network models of embryogenesis and stem cell differentiation
• relating gut bacterial populations to diet and health.

Read about Complex Systems Science: A new way of thinking.