Difference between revisions of "Mathematical and theoretical biology"
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Describing systems in a quantitative manner means their behavior can be better simulated, and hence properties can be predicted that might not be evident to the experimenter. | Describing systems in a quantitative manner means their behavior can be better simulated, and hence properties can be predicted that might not be evident to the experimenter. | ||
| − | Mathematical biology may deploy [[calculus]], [[probability theory]], [[statistics]], [[linear algebra]], [[abstract algebra]], [[graph theory]], [[combinatorics]], [[algebraic geometry]], [[topology]], [[dynamical systems]], [[differential equations | + | Mathematical biology may deploy [[calculus]], [[probability theory]], [[statistics]], [[linear algebra]], [[abstract algebra]], [[graph theory]], [[combinatorics]], [[algebraic geometry]], [[topology]], [[dynamical systems]], [[differential equations]] and [[coding theory]]. |
Some mathematical areas, such as certain methodologies in statistics, were developed as tools during the conduct of research into mathematical biology. | Some mathematical areas, such as certain methodologies in statistics, were developed as tools during the conduct of research into mathematical biology. | ||
Revision as of 17:09, 27 April 2016
Mathematical and theoretical biology is an interdisciplinary scientific research field combining [[[mathematics]] and biology, with a range of applications in biology, biotechnology, and medicine.
The field is also called mathematical biology or biomathematics to stress the mathematical side, or theoretical biology to stress the biological side.
Description
Mathematical biology aims at the mathematical representation, treatment and modeling of biological processes, using a variety of applied mathematical techniques and tools.
It has both theoretical and practical applications in biological, biomedical and biotechnology research.
For example, in cell biology, protein interactions are often represented as "cartoon" models, which, although easy to visualize, do not accurately describe the systems studied. This requires precise mathematical models.
Describing systems in a quantitative manner means their behavior can be better simulated, and hence properties can be predicted that might not be evident to the experimenter.
Mathematical biology may deploy calculus, probability theory, statistics, linear algebra, abstract algebra, graph theory, combinatorics, algebraic geometry, topology, dynamical systems, differential equations and coding theory.
Some mathematical areas, such as certain methodologies in statistics, were developed as tools during the conduct of research into mathematical biology.
See also
- Artificial life
- Bio-inspired computing
- Biological applications of bifurcation theory
- Biostatistics
- Cellular automaton
- Computational biology
- Computational gene
- DNA computing
- Ewens's sampling formula
- Journal of Theoretical Biology
- Mathematical modelling of infectious disease
- Metabolic network modelling
- Molecular modelling
- Morphometrics
- Population genetics
- Protein folding
- Quantum Biology
- Simulated reality
- Statistical genetics
- Systems biology
- Theoretical ecology
External links
- Mathematical and theoretical biology @ Wikipedia
