Journal
PROCESSES
Volume 2, Issue 4, Pages 711-752Publisher
MDPI AG
DOI: 10.3390/pr2040711
Keywords
microbial communities; mathematical models; dynamics; integrative modeling approaches
Categories
Funding
- Genomic Science Program (GSP)
- Office of Biological and Environmental Research (OBER)
- U.S. Department of Energy (DOE)
- U.S. Department of Energy [DE-AC06-76RLO]
Ask authors/readers for more resources
Microorganisms in nature form diverse communities that dynamically change in structure and function in response to environmental variations. As a complex adaptive system, microbial communities show higher-order properties that are not present in individual microbes, but arise from their interactions. Predictive mathematical models not only help to understand the underlying principles of the dynamics and emergent properties of natural and synthetic microbial communities, but also provide key knowledge required for engineering them. In this article, we provide an overview of mathematical tools that include not only current mainstream approaches, but also less traditional approaches that, in our opinion, can be potentially useful. We discuss a broad range of methods ranging from low-resolution supra-organismal to high-resolution individual-based modeling. Particularly, we highlight the integrative approaches that synergistically combine disparate methods. In conclusion, we provide our outlook for the key aspects that should be further developed to move microbial community modeling towards greater predictive power.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available