LAPSE:2018.0258
Published Article
LAPSE:2018.0258
Modeling Microbial Communities: A Call for Collaboration between Experimentalists and Theorists
Marco Zaccaria, Sandra Dedrick, Babak Momeni
July 31, 2018
With our growing understanding of the impact of microbial communities, understanding how such communities function has become a priority. The influence of microbial communities is widespread. Human-associated microbiota impacts health, environmental microbes determine ecosystem sustainability, and microbe-driven industrial processes are expanding. This broad range of applications has led to a wide range of approaches to analyze and describe microbial communities. In particular, theoretical work based on mathematical modeling has been a steady source of inspiration for explaining and predicting microbial community processes. Here, we survey some of the modeling approaches used in different contexts. We promote classifying different approaches using a unified platform, and encourage cataloging the findings in a database. We believe that the synergy emerging from a coherent collection facilitates a better understanding of important processes that determine microbial community functions. We emphasize the importance of close collaboration between theoreticians and experimentalists in formulating, classifying, and improving models of microbial communities.
Keywords
community ecology, interspecies interactions, mathematical modeling, mechanistic modeling, microbial communities, phenomenological modeling
Subject
Suggested Citation
Zaccaria M, Dedrick S, Momeni B. Modeling Microbial Communities: A Call for Collaboration between Experimentalists and Theorists. (2018). LAPSE:2018.0258
Author Affiliations
Zaccaria M: Department of Biology, Boston College, Chestnut Hill, MA 02467, USA
Dedrick S: Department of Biology, Boston College, Chestnut Hill, MA 02467, USA
Momeni B: Department of Biology, Boston College, Chestnut Hill, MA 02467, USA [ORCID]
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Journal Name
Processes
Volume
5
Issue
4
Article Number
E53
Year
2017
Publication Date
2017-09-25
Published Version
ISSN
2227-9717
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PII: pr5040053, Publication Type: Comment
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LAPSE:2018.0258
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doi:10.3390/pr5040053
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Jul 31, 2018
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CC BY 4.0
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