Manuscript Topics
Mathematics can easily intertwine with developing sciences, with each incremental interaction enhancing that particular field. Biomedical science, for example, has raised to a paramount application framework. To keep the momentum towards scientific progress, mathematicians and engineers must become involved with biology. Mathematical biology is a fascinating fast-growing subject and the increasing involvement of mathematics is inevitable as biology becomes more quantitative. The complexity of the biology leads to mandatory interdisciplinarity: for the mathematician and the engineer, biology opens up new and exciting horizons, while for the biologist, mathematical modelling offers a new implementation tool which will help leaning towards virtual representation of laboratory processes.

In particular, the complexity of biology translates easily into multivariable functions, whose variation into a multidimensional domain, leads to partial differential equations (PDEs). As it is generally impossible to integrate PDEs in closed form, there is a vast amount of modern mathematical and scientific research on methods to numerically approximate solutions of certain partial differential equations using computers. This Special Issue of Mathematical and Biosciences and Engineering is precisely devoted to PDEs as applied in a variety of scientific and technological fields associated with the branches of Biology, presenting a variety of deterministic models. A wide spectrum of different types of PDEs and related solution methods have been presented, including elliptic and parabolic PDEs etc.......

Numerous examples are drawn from population ecology, reaction kinetics, biological oscillators, developmental biology, evolution, epidemiology and other areas. In general, models provide biological insight and are very useful in summarizing, interpreting and interpolating real data. No previous knowledge of biology is assumed of the reader. With each paper presented herein, a brief description of the biological background will be given sufficient to understand the models studied.

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