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Mathematical and Theoretical Biology

Mathematical and theoretical biology is an interdisciplinary scientific research field with a range of applications in the fields of biology, biotechnology, and medicine. The field may be referred to as mathematical biology or biomathematics to stress the mathematical side or as theoretical/ hypothetical biology to stress the biological side. It includes at least 4 major subfields: biological mathematical modeling, complex systems biology (CSB), bioinformatics and computational biomodeling or biocomputing. Mathematical biology has aim at the mathematical representation treatment and modeling of biological processes, using several applied mathematical methods and tools. It has practical and theoretical applications in biotechnology, biological and biomedical research. For illustration, in cell biology the protein interactions are often represented as "cartoon" models, which, though easy to visualize and do not accurately describe the systems studied. To do this, precise mathematical models are required. By describing systems in a quantitative manner their behaviour can be better simulated and hence properties can be predicted that might not be evident to the experimenter.

This type of mathematical areas such as calculus, probability theory, statistics, linear algebra, algebraic geometry, abstract algebra, graph theory, combinatorics, dynamical systems, differential equations, topology and coding theory are now being applied in biology. Some mathematical areas, like statistics, were developed as tools during the conduct of research into mathematical biology.

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Importance

Applying mathematics to biology has a long history, but recently has there been an explosion of interest in the field. Some reasons for this includes:

The explosion of data-rich information sets, because of the genomics revolution, which are not easy to understand without the use of analytical tools, Recent development of mathematical tools such as chaos theory to help understand complex, that is non-linear mechanisms in biology, an increase in computing power which enables calculations and simulations to be performed that were not previously possible, and an increasing interest in silico experimentation due to ethical considerations, risk, unreliability and other complications involved in human and animal research.

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