Advances in technologies for molecular observation are leading to novel types of data, including gene, transcript, protein, and metabolite levels, which are fundamentally different from the types traditionally compared with microbial ecosystem models, such as biomass (e.g., chlorophyll a) and nutrient concentrations. A grand challenge is to use these data to improve predictive models and use models to explain observed patterns. This article presents a framework that aligns observations and models along the dimension of abstraction or biological organization-from raw sequences to ecosystem patterns for observations, and from sequence simulators to ecological theory for models. It then reviews 16 studies that compared model results with molecular observations. Molecular data can and are being combined with microbial ecosystem models, but to keep up with and take advantage of the full scope of observations, models need to become more mechanistically detailed and complex, which is a technical and cultural challenge for the ecological modeling community.

中文翻译：

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结合分子观察和微生物生态系统建模：实用指南。

分子观测技术的进步导致了新的数据类型，包括基因，转录本，蛋白质和代谢产物水平，这些数据与传统上与微生物生态系统模型（例如生物量（例如叶绿素a）和营养素）相比的类型根本不同。浓度。一个巨大的挑战是使用这些数据来改进预测模型并使用模型来解释观察到的模式。本文提供了一个框架，该框架沿抽象或生物组织的维度调整观测和模型-从原始序列到观测的生态系统模式，从序列模拟器到模型的生态理论。然后，它回顾了将模型结果与分子观察结果进行比较的16项研究。分子数据可以并且正在与微生物生态系统模型结合，