Special Issue: Mathematical foundations in biological modelling and simulation
Guest Editors
Prof. Gilberto González-Parra
Department of Mathematics, New Mexico Institute of Mining and Technology, New Mexico, USA
Email: Gilberto.GonzalezParra@nmt.edu
Prof. Hana M. Dobrovolny
Dept. of Physics & Astronomy, Texas Christian University, TX 76129, USA
Email: h.dobrovolny@tcu.edu
Manuscript Topics
The current COVID-19 pandemic has made it clear that biological modeling in conjunction with computational simulation plays an important role in life sciences. Biological modeling helps with the qualitative and quantitative understanding of many biosystems. Biological modeling deals with a variety of topics that includes cells, viruses, parasites, many different types of pathogens, human body, animals, ecosystems, etc. In the past, biological models have provided valuable information for public health and improving quality of life. The high complexity of biological systems requires in many cases the use of biological modeling and simulations since theoretical analysis is intractable. Thus, these computer simulations of biosystems provide an excellent tool to get deeper insight in the understanding of many biological processes.
In this Special Issue, we will include recent developments of biological modeling techniques and computer simulations for a variety of biological systems at different biological scales. The high complexity of biological systems makes them an ideal topic for testing biological theoretical models through simulations. There are many simulation techniques/algorithms that can be used for the simulation of biological models and new ones are constantly being developed. Finally, the simulations require biological interpretation and validation of the results. Ideally, a biological theoretical model should be compared with experimental biological data. Thus, in this special issue we solicit prospective authors to submit original papers mainly dealing with, but not limited to, the following topics:
• Dynamical systems for a variety of populations such as humans, cells, animals, parasites, etc.
• Models for biological systems
• Algorithms based on biological systems
• Algorithms for simulation of deterministic or stochastic biological models
Instructions for authors
https://www.aimspress.com/mbe/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
https://aimspress.jams.pub/