Survey of Engineering Models for Systems Biology. (18th January 2016)

• Record Type: Journal Article
• Authors: Reeves, Gregory T.; Hrischuk, Curtis E.
• Other Names: Purohit Rituraj Academic Editor.
• Is Part Of: Computational biology journal. Volume 2016(2016)
• Publication Date: 2016-01-18
• Subjects: Computational biology -- Periodicals; Computational biology; Biología -- Publicaciones periódicas; Ciencias -- Publicaciones periódicas; Periodicals; Electronic journals; 570.285
• DOI: 10.1155/2016/4106329
• Languages: English
• ISSNs: 2314-4165

Abstract

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.