ABSTRACT

This chapter starts the third part of the book that covers the remaining design-automation challenges, namely protocol parameter-space co-optimization and real-time error recovery. In this chapter, the focus is drawn on introducing a design-automation flow for protocol parameter-space co-optimization, which is especially useful for enabling biomolecular analysis using synthetic biocircuits. A fundamental challenge in building reliable biocircuits has been the lack of cost-effective design methodologies that enable optimal configuration of gene-regulatory parameters. Such a configuration can be obtained only using a systematic microfluidic assay, named biocircuit-regulatory scanning (BRS), that produces numerous (and representative) reagent mixtures to modulate the parameter space of a biocircuit. The design flow proposed in this chapter addresses the above challenge using: (1) a statistical method that computes volumetric ratios of reagents in each mixture droplet; (2) an Integer Linear Programming (ILP)-based synthesis method that implements a BRS assay on a MEDA biochip; and (3) an iterative decision-making utility based on regression analysis to control the accuracy of the parameter-space. Simulation results show that the proposed flow efficiently utilizes reagent fluids and enhances the prediction accuracy of a parameter space.