ABSTRACT
This chapter starts the second part of the book that focuses on design optimization for single-cell analysis and support for sample differentiation. In this chapter, design of a hybrid cyber-physical microfluidic platform is provided, enabling complete single-cell analysis on a heterogeneous pool of cells. This architecture is combined with an associated design-automation and optimization framework, referred to as Co-Synthesis (CoSyn), which facilitates scalable sample indexing/barcoding. The proposed framework employs real-time resource allocation to coordinate the progression of concurrent cell analysis. This chapter also discusses realistic experimental settings where protocol conditions are specified in a probabilistic manner. To address these settings, a probabilistic model of single-cell analysis based on discrete time Markov chains (DTMCs) is presented. Simulation results show that CoSyn efficiently utilizes platform resources and outperforms baseline techniques
