Bhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, Indian Institute of Technology (IIT) Madras, Chennai 600 036, India.
Centre for Integrative Biology and Systems mEdicine, IIT Madras, Chennai 600 036, India.
ACS Synth Biol. 2024 Aug 16;13(8):2260-2270. doi: 10.1021/acssynbio.4c00116.
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.
微生物群落由于其广泛存在和对生命各个方面的深远影响而非常重要。理解这些复杂系统需要数学建模,这是模拟和预测微生物群落行为的有力工具。本综述对代谢建模进行了批判性分析,并强调了将从更广泛的讨论和协作中受益的关键领域。此外,我们还探讨了与这些群落的复杂性质相关的挑战和机遇,涵盖了数据生成、建模和验证。我们相信,建模技术的不断进步,如机器学习,加上跨学科合作,将释放微生物群落在各种应用中的全部潜力。