Predicting the outcome of an observable phenomenon belongs to the key disciplines of natural sciences. A chemist can precisely calculate the temperature increase when dehydrating sugars upon contact with sulfuric acid. A physicist can predict the force needed to leverage a rock of a certain weight. But for a biologist, the situation is different. It is an excessively difficult and time-consuming task to perform detailed calculations on biological systems. For a long time, it was even believed that a mysterious vital spark drives all living entities.
So what makes calculations in biology so different from other sciences? Living entities belong to the most complex systems in existence. At the most basic level, a single cell comprises huge numbers of molecules and is structured in a very densely organized space, All those molecules participate in a numerous biochemical reactions, highly regulated enzymes drive these reactions, and
external signals interfere with the cell, in the form of hormones, drugs, or variations in the amount of nutrition available.
It is not possible for the human mind to keep track of so many processes in parallel. So, how can we calculate effects of cellular functions? The most viable option is to construct highly detailed computer models that facilitate visualization and statistics to see trends, and mathematical modeling to precisely calculate interactions of components to predict system behavior.
In order to be reliable and diagnostically conclusive, these models need to be constricted to real-world conditions by incorporating physicochemical constraints. However, the complexity of the interactions can still be overwhelming.
Yet, making biological phenomena predictable is worthwhile. By simulating entire cellular systems we could: Gain a better understanding of the system in its entirety. Calculate how much medicine a patient should take in order to avoid adverse effects, or Determine potential weaknesses of harmful pathogens as a precursor for drug development.
To this end, the University of Tuebingen and the University of California, San Diego, established a joint project with the aim of developing new computational methods that make it possible to model all levels of biological systems.
As the result, a wide range of software and database solutions have been created that make building and analyzing systems biology models much more straightforward.
For more information, or to download and try systems biology software, visit http://systems-biology.info