系统生物学的工程设计方法。

IF 1.4 4区 生物学 Q4 CELL BIOLOGY
Kevin A Janes, Preethi L Chandran, Roseanne M Ford, Matthew J Lazzara, Jason A Papin, Shayn M Peirce, Jeffrey J Saucerman, Douglas A Lauffenburger
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引用次数: 0

摘要

测量和模拟生物分子-细胞网络的综合行为是系统生物学的核心。几十年来,定量生物学家、物理学家、数学家和工程师以不同的方式塑造了系统生物学。然而,系统生物学的基础版本和应用版本通常没有区分开来,这就模糊了该领域的不同愿望及其对现实世界的潜在影响。在这里,我们阐述了系统生物学的工程学方法,它应用教育理念、工程设计和预测模型来解决生物医学大数据时代的当代问题。培养系统生物工程师的共同努力将提供一支多才多艺的人才队伍,能够应对现代信息密集型经济中生物技术和制药部门所面临的各种挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An engineering design approach to systems biology.

An engineering design approach to systems biology.

An engineering design approach to systems biology.

Measuring and modeling the integrated behavior of biomolecular-cellular networks is central to systems biology. Over several decades, systems biology has been shaped by quantitative biologists, physicists, mathematicians, and engineers in different ways. However, the basic and applied versions of systems biology are not typically distinguished, which blurs the separate aspirations of the field and its potential for real-world impact. Here, we articulate an engineering approach to systems biology, which applies educational philosophy, engineering design, and predictive models to solve contemporary problems in an age of biomedical Big Data. A concerted effort to train systems bioengineers will provide a versatile workforce capable of tackling the diverse challenges faced by the biotechnological and pharmaceutical sectors in a modern, information-dense economy.

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来源期刊
Integrative Biology
Integrative Biology 生物-细胞生物学
CiteScore
4.90
自引率
0.00%
发文量
15
审稿时长
1 months
期刊介绍: Integrative Biology publishes original biological research based on innovative experimental and theoretical methodologies that answer biological questions. The journal is multi- and inter-disciplinary, calling upon expertise and technologies from the physical sciences, engineering, computation, imaging, and mathematics to address critical questions in biological systems. Research using experimental or computational quantitative technologies to characterise biological systems at the molecular, cellular, tissue and population levels is welcomed. Of particular interest are submissions contributing to quantitative understanding of how component properties at one level in the dimensional scale (nano to micro) determine system behaviour at a higher level of complexity. Studies of synthetic systems, whether used to elucidate fundamental principles of biological function or as the basis for novel applications are also of interest.
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