Applications of Stochastic Processes in Biology and Medicine
1Department of Mathematics, Drexel University, Philadelphia, PA, USA
2Department of Mathematics, Duke University, Durham, NC, USA
3School of Mathematical Sciences, Monash University, Melbourne, VIC, Australia
4Department of Mathematics, Trinity University, San Antonio, TX, USA
Applications of Stochastic Processes in Biology and Medicine
Description
Biological processes, encountered in fields of biology and medicine, are characterized by variability and uncertainty, which provide fertile ground for applications of stochastic processes. Also, along with the development of computers with increasing memory capacities and increasing speed of execution, computer-intensive research methods in biology and medicine are becoming more mathematized in attempts to cope with complexities that arise in these fields of research. The aim of this special issue is to put together review papers as well as papers on original research on applications of stochastic processes as models of dynamic phenomena that are encountered in biology and medicine.
Submission of papers on applications of stochastic processes in various fields of biology and medicine will be welcome. Potential topics include, but are not limited to:
- Evolutionary and population genetics
- Models of epidemics of infectious diseases
- Strategies of controlling epidemics
- Evolution of populations in space and time
- Applications of graph theory and papers in chemistry and physics pertaining dating materials in connection with biological and cosmic evolution
- Applications of stochastic processes in cancer research
- Branching processes, especially those that are self-regulatory or population density dependent or that include movement of individuals in space and time
There is a number of subfields of stochastic processes that have applications, either realized or potential, in biology and medicine. Review papers by experts on these developing subfields will also be welcome.
An example of a developing subfield of evolutionary and population genetics is that of the development of stochastic processes describing the evolution of genomes. Among other things, stochastic models of nucleotide substitutions, deletions, insertions, and repeats of segments of DNA along with inversions and translocation within and among chromosomes as well as gene conversions need to be included in formulation of stochastic models of genomic evolution. Review papers or papers involving new approaches to genomic evolution will be welcome.
Papers on applying the Monte Carlo simulation methods will be welcome only if the mathematical algorithms underlying these methods are fully disclosed. For example, the mathematics underling a Monte Carlo simulation model should be presented in sufficient detail such that, in principle, any investigator could write software in a programming language of his or her choosing to verify the validity of the results in any reported simulation experiment.
Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/ijsa/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following timetable: