AI 中文总结
DigiPhen平台是构建生物系统预测模型的新范式，通过集成工作流构建生物数字表征，可预测遗传与环境变化对细胞表型的影响，助力生物系统再工程。
AI 中文摘要
经基因工程改造的生物系统有潜力彻底变革化学与材料生产、提升关键矿物回收率、充当威胁传感器并改善人类健康。然而，生物体的极端复杂性使得除最简单情况外，难以实现这一潜力。不过，近期技术进步为解决该问题奠定了基础。本文介绍了一种可加速细胞再工程的能力，它能准确预测遗传或环境变化对细胞表型的影响。该数字表型组平台（DigiPhen）由集成的实验、分析与建模工作流构成，用于构建微生物或植物系统的数字表征。其围绕不断扩展的可互换、互联软件及实验模块设计，这些模块能准确表征表型的机制决定因素。DigiPhen平台将以半自主方式系统收集细胞组成、空间组织、代谢通路及调控网络的数据，并利用这些信息构建模块化、多尺度的生物系统模型。这些模型将用于预测产生 desired 生物结果所需的分子与环境变化。DigiPhen旨在成为社区研究活动的核心，既能满足个体研究者的即时需求，又能实现科学界的长期目标。总体而言，DigiPhen平台代表了构建生物系统预测模型的新范式。
英文摘要
Reengineered biological systems have the potential to revolutionize chemical and material production, enhance critical mineral recovery, serve as threat sensors and improve human health. Unfortunately, the extreme complexity of organisms has made it difficult to achieve this potential in all but the simplest cases. Recent technological advances, however, have provided a foundation for solving this problem. Here, we describe a capability for accelerating the reengineering of cells by providing accurate predictions of the impact of genetic or environmental changes on cell phenotype. This digital phenome platform (DigiPhen) consists of integrated experimental, analytical and modeling workflows for building a digital representation of microbial or plant systems. It is designed around an expanding set of interchangeable, interconnecting software and experimental modules that can accurately represent the mechanistic determinants of phenotype. The DigiPhen platform will systematically collect data on cell composition, spatial organization, metabolic pathways and regulatory networks in a semi-autonomous fashion and use this information to build modular, multi-scale models of biological systems. These models will be used to predict molecular and environmental changes needed for producing desired biological outcomes. DigiPhen is intended to be the heart of community research campaigns that will meet the immediate needs of individual researchers while fulfilling long-term goals of the scientific community. Altogether, the DigiPhen platform represents a new paradigm for building predictive models of biological systems.
Comments18 pages, 1 figure and 1 table
