Modeling Microbial Communities: Perspective and Challenges

被引:9
作者
Raajaraam, Lavanya [1 ,2 ,3 ]
Raman, Karthik [1 ,2 ,3 ,4 ]
机构
[1] Indian Inst Technol IIT Madras, Bhupat & Jyoti Mehta Sch Biosci, Dept Biotechnol, Chennai 600036, India
[2] IIT Madras, Ctr Integrat Biol & Syst Med, Chennai 600036, India
[3] IIT Madras, Robert Bosch Ctr Data Sci & Artificial Intelligenc, Chennai 600036, India
[4] IIT Madras, Wadhwani Sch Data Sci & Artificial Intelligence, Dept Data Sci & AI, Chennai 600036, India
关键词
metabolic modeling; genome-scale models; metabolicengineering; constraint-based modeling; microbiome; microbial consortia; machine learning; FLUX ANALYSIS; METABOLISM;
D O I
10.1021/acssynbio.4c00116
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Microbial communities are immensely important due to their widespread presence and profound impact on various facets of life. Understanding these complex systems necessitates mathematical modeling, a powerful tool for simulating and predicting microbial community behavior. This review offers a critical analysis of metabolic modeling and highlights key areas that would greatly benefit from broader discussion and collaboration. Moreover, we explore the challenges and opportunities linked to the intricate nature of these communities, spanning data generation, modeling, and validation. We are confident that ongoing advancements in modeling techniques, such as machine learning, coupled with interdisciplinary collaborations, will unlock the full potential of microbial communities across diverse applications.
引用
收藏
页码:2260 / 2270
页数:11
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