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- W2259670429 abstract "In recent years, the field of systems biology has emerged from a confluence of an increase both in molecular biotechnology and in computing storage and power. As a discipline, systems biology shares many characteristics with engineering. However, before the benefits of engineering-based modeling formalisms and analysis tools can be applied to systems biology, the engineering discipline(s) most related to systems biology must be identified. In this paper, we identify the cell as an embedded computing system and, as such, demonstrate that systems biology shares many aspects in common with computer systems engineering, electrical engineering, and chemical engineering. This realization solidifies the grounds for using modeling formalisms from these engineering subdisciplines to be applied to biological systems. While we document several examples where this is already happening, our goal is that identifying the cell as an embedded computing system would motivate and facilitate further discovery through more widespread use of the modeling formalisms described here." @default.
- W2259670429 created "2016-06-24" @default.
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- W2259670429 date "2016-01-18" @default.
- W2259670429 modified "2023-10-16" @default.
- W2259670429 title "Survey of Engineering Models for Systems Biology" @default.
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- W2259670429 doi "https://doi.org/10.1155/2016/4106329" @default.
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