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Survey of Engineering Models for Systems Biology
Author(s) -
Gregory T. Reeves,
Curtis Hrischuk
Publication year - 2016
Publication title -
computational biology journal
Language(s) - English
Resource type - Journals
eISSN - 2314-4173
pISSN - 2314-4165
DOI - 10.1155/2016/4106329
Subject(s) - rotation formalisms in three dimensions , systems biology , biological systems engineering , synthetic biology , computer science , realization (probability) , system of systems engineering , modelling biological systems , field (mathematics) , biological engineering , software engineering , data science , systems engineering , biology , engineering , computational biology , systems design , bioinformatics , artificial intelligence , mechatronics , mathematics , statistics , geometry , pure mathematics
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

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