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.
Highlights
Science progresses by developing predictive models of reality to refine and validate hypotheses
We find that there are instances where such embedded system modeling formalisms are already being used in systems biology research and cite these specific examples
Systems biology necessarily relies on using modeling formalisms to synthesize data into a consistent mathematical framework
Summary
Science progresses by developing predictive models of reality to refine and validate hypotheses. Regardless, it would be helpful to identify an engineering discipline that is most like systems biology so that the related engineering processes and tools can be assessed for use within systems biology. Just as engineering consists of more than one discipline, there are many different definitions for systems biology comprising cycles of modeling, prediction, and experiment (see [4, 13,14,15,16]). We find that there are instances where such embedded system modeling formalisms are already being used in systems biology research and cite these specific examples. This validates that embedded system engineering best practices and modeling techniques are applicable to systems biology. Throughout the paper, we use the term contemporary to refer to those computational things with which we are familiar, while the term cellular refers to things that are like contemporary computing elements but the context is within the cell
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