Algorithmic systems biology

The quantitative algorithmic descriptions of biological processes add causal, spatial, and temporal dimensions to molecular machinery's behavior to facilitate understanding of life by transforming collections of pictures into spectacular films. The systems biology is a transition from qualitative biology, reductionism to system-level, structural and static descriptions thereby highlighting the causality between events. Such algorithms precisely describe the behavior of systems with discrete state spaces, thereby relying on a sequential modeling style to describe an inherently concurrent system. These integrated systems can be easily embedded with bioinformatics in the modeling of the immune system, in addition to the dimensions of time and space. Algorithmic systems biology can help understand about life sciences and natural sciences through interconnecting models and experiments, employed by life scientists to predict the behavior life scientists to predict the behavior systems.