<unk>  is a significant task of<unk>  biology and mathematical biology. Computational<unk>  biology aims to develop and use efficient algorithms, data structures, visualization and communication tools with the goal of computer<unk>  of<unk><unk> . It involves the use of computer simulations of<unk><unk> , including cellular subsystems (such as the networks of metabolites and enzymes which comprise metabolism, signal transduction pathways and gene regulatory networks), to both analyze and visualize the complex connections of these cellular processes. An unexpected emergent property of a complex<unk> may be a result of the interplay of the cause-and-effect among simpler, integrated parts (see<unk>  organisation).<unk><unk>  manifest many important examples of emergent properties in the complex interplay of components. Traditional study of<unk><unk>  requires reductive methods in which quantities of data are gathered by category, such as concentration over time in response to a certain stimulus. Computers are critical to analysis and<unk>  of these data. The goal is to create accurate real-time models of a<unk> s response to environmental and internal stimuli, such as a model of a cancer cell in order to find weaknesses in its signalling pathways, or<unk>  of ion channel mutations to see effects on cardiomyocytes and in turn, the function of a beating heart.
Modelling biological systems
Discovery of disease-causing pathogens
Personal health application
Clinical engineering
Use of technology in treatment of mental disorders
Wireless device radiation and health
Injury prevention
Clean living movement