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- Modeling and Simulation
- Computer Science Applications
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Stochastic Models in Mathematical Biology : Preface. / Gani, J.; Haynatzka, V. R.; Haynatzki, G. R.; Rachev, S. T.In: Mathematical and Computer Modelling, Vol. 32, No. 1-2, 11.07.2000, p. xiii.
Research output: Contribution to journal › Editorial › peer-review
TY - JOUR
T1 - Stochastic Models in Mathematical Biology
T2 - Preface
AU - Gani, J.
AU - Haynatzka, V. R.
AU - Haynatzki, G. R.
AU - Rachev, S. T.
N1 - Funding Information: The past decade has witnessed a vast increase in the application of mathematical methods to biology. The contribution of biomedical research to the improvement of public health has been widely recognized. The number of papers in biomedical, biomathematical, and biostatistical journals has greatly increased, and in the United States, for example, funding for the National Institutes of Health (NIH) has been substantially improved in recent years. Despite this, certain diseases, such as AIDS and cancer, have proved difficult to analyze by existing methods; new methods, with a greater mathematical content are emerging. The complexity of biological systems and the variability in individual responses of members of the same species within the same environment lead one to conclude that mathematical methods are indispensable in biological and biomedical research. Of the many mathematical models in biology, stochastic models have enjoyed the greatest attention because they appear to capture reality most closely. But if they are to be of use to biologists, such models must be kept as simple as possible. The primary purpose of this special issue is to provide a forum for researchers, active in the area of biological modeling, to discuss their recent work on such simple and more complex models. This issue is also intended to stimulate research in the area. We have been conscious for some time that both researchers and students are not fully aware of the richness of stochastic models currently in use; we hope to remedy this deficiency in this issue. Accordingly, researchers working on a wide range of problems of mathematical biology were invited to submit their papers for publication. This special issue begins with some methodological papers and continues with papers on topics in mathematical genetics, cell kinetics, epidemic models, and mathematical methods in both cancer and environmental research. These classifications are inevitably dictated by our personal perspectives, and it is possible that some authors and readers may not agree with all of them. It was not our intention to classify contributions into rigid categories, and on several occasions we had some difficulty in determining the appropriate category. Each paper stands on its own merits, and we hope that readers will enjoy the issue and derive some benefit from it. In conclusion, we as editors of this issue, should like to thank every one of the contributors, as well as the Editor-in-Chief of Mathematical and Computer Modelling, Ervin Y. Rodin, for his unfailing support. Restrictions of space have prevented us from accepting a larger number of papers, but we hope to continue our editorial enterprise with a second and possibly a third issue on Stochastic Models in Mathematical Biology. We would welcome further contributions and suggestions. One of the editors, Gleb R. Haynatzki, would like to record his gratitude for support from McMaster University, Canada and The State of Nebraska Cancer and Smoking-Diseases Grant.
PY - 2000/7/11
Y1 - 2000/7/11
UR - http://www.scopus.com/inward/record.url?scp=0034636717&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0034636717&partnerID=8YFLogxK
U2 - 10.1016/S0895-7177(00)00115-1
DO - 10.1016/S0895-7177(00)00115-1
M3 - Editorial
AN - SCOPUS:0034636717
VL - 32
SP - xiii
JO - Mathematical and Computer Modelling
JF - Mathematical and Computer Modelling
SN - 0895-7177
IS - 1-2