Data Model Standardization for Synthetic Biomolecular Circuits and Systems

Abstract

While biological engineers strive to capture the biophysical theory essential in predicting how a newly designed synthetic organism will behave, the current state of this knowledge is far from ideal. To facilitate the research towards this goal, specifically through the application of computational tools, the data required to engineer biological systems should be electronically accessible and interpretable. The challenge to represent such information computationally is complicated by the enormous diversity and size of biological data. There is a plethora of biological components, interacting physically and chemically, with implications for behavior at multiple time and spatial scales. The many scientists working to move the synthetic biology field forward have to communicate their research findings and should understand each other despite their diverse academic backgrounds. The challenge and demand for data standardization arises from the need to collaborate in order to engineer ever more complex biomolecular circuits and to understand and control biological systems. The bioinformatics field provides us with a history of experience in its attempts to facilitate collaboration in the biomedical research community. We draw on the lessons from the application of information technology solutions to inform and inspire the new efforts in synthetic biology. Furthermore, we acknowledge fundamental differences in the nature of the two fields and discuss the need to standardize data models for the purpose of engineering and design of novel biomolecular circuits and systems.