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Mathematical and theoretical biology, or biomathematics, is a branch of biology which employs theoretical analysis, mathematical models and abstractions of living organisms to investigate the principles that govern the structure, development and behavior of the systems, as opposed to experimental biology which deals with the conduction of ...
1.1 Mathematics. 1.2 Physics. 1.3 Chemistry. 1.4 Biology. 1.5 Economics. 2 Other equations. ... The following equations are named after researchers who discovered them.
The same set of equations was published in 1926 by Vito Volterra, a mathematician and physicist, who had become interested in mathematical biology. [13] [18] [19] Volterra's enquiry was inspired through his interactions with the marine biologist Umberto D'Ancona, who was courting his daughter at the time and later was to become his son-in-law.
Together, Lotka and Volterra formed the Lotka–Volterra model for competition that applies the logistic equation to two species illustrating competition, predation, and parasitism interactions between species. [3] In 1939 contributions to population modeling were given by Patrick Leslie as he began work in biomathematics.
Differential equations play a prominent role in many scientific areas: mathematics, physics, engineering, chemistry, biology, medicine, economics, etc. This list presents differential equations that have received specific names, area by area.
Population dynamics is a branch of mathematical biology, and uses mathematical techniques such as differential equations to model behaviour. Population dynamics is also closely related to other mathematical biology fields such as epidemiology, and also uses techniques from evolutionary game theory in its modelling.
Pages in category "Mathematical and theoretical biology" The following 84 pages are in this category, out of 84 total. This list may not reflect recent changes .
The McKendrick–von Foerster equation is a linear first-order partial differential equation encountered in several areas of mathematical biology – for example, demography [1] and cell proliferation modeling; it is applied when age structure is an important feature in the mathematical model. [2]