Mathematical and computational modeling in biology at multiple scales.

Jack A Tuszynski,Chih-Yuan Tseng,Mariusz Klobukowski,Kamlesh K Sahu,Diana White,Philip Winter,Ivana Spasevska,Cassandra Dm Churchill,Francesco Gentile,Sara Ibrahim Omar,Rabab M Abou El-Magd,Niloofar Nayebi

doi:10.1186/1742-4682-11-52

Abstract

A variety of topics are reviewed in the area of mathematical and computational modeling in biology, covering the range of scales from populations of organisms to electrons in atoms. The use of maximum entropy as an inference tool in the fields of biology and drug discovery is discussed. Mathematical and computational methods and models in the areas of epidemiology, cell physiology and cancer are surveyed. The technique of molecular dynamics is covered, with special attention to force fields for protein simulations and methods for the calculation of solvation free energies. The utility of quantum mechanical methods in biophysical and biochemical modeling is explored. The field of computational enzymology is examined.

Highlights

Mathematical, computational and physical methods have been applied in biology and medicine to study phenomena at a wide range of size scales, from the global human population all the way down to the level of individual atoms within a biomolecule
Molecular dynamics is often used to model biomolecules as a system of moving Newtonian particles with interactions defined by a force field, with various methods employed to handle the challenge of solvent effects
In order to follow the motions of every atom and molecule over extremely small timescales, computational methods such as molecular dynamic simulations can be applied

Summary

Introduction

Mathematical, computational and physical methods have been applied in biology and medicine to study phenomena at a wide range of size scales, from the global human population all the way down to the level of individual atoms within a biomolecule. The simplest type of model that can be used to describe how cancer cells of a solid tumor change over time is the exponential growth law, given by equation (23) Such an equation is limited in its application, since it suggests that tumors grow (with growth rate r) to a tumor of unbounded size. Some models for solid tumor growth have included such information by incorporation of reaction-diffusion type equations, like equation (26) This latter model, studied by Murray [26], was developed to describe the spatio-temporal invasion of gliomas. In order to follow the motions of every atom and molecule over extremely small timescales, computational methods such as molecular dynamic simulations (designed to solve extremely large systems of differential equations over very small timescales) can be applied Often, such methods are highly inaccurate for reaction barriers and energies but their accuracy can be improved significantly by re-parameterization for a specific reaction

Conclusions

Caticha A

31. Soper HE

Methods

70. Casey AE

74. Chaplain MAJ