Fast and Accurate Circuit Design Automation through Hierarchical Model Switching

Area of Science:

• Synthetic Biology
• Computational Biology
• Bioengineering

Background:

• Reliable biological design requires characterized parts, accurate models, and optimal parameters.
• Increasing complexity in biological parts and models hinders efficient design optimization.
• Existing methods face challenges in searching large solution spaces for complex biological systems.

Purpose of the Study:

• To present a novel hierarchical computer-aided design (CAD) architecture for biological design.
• To overcome the computational complexity trade-off in optimizing biological circuits.
• To enable efficient and accurate design of complex biological systems.

Main Methods:

• A two-step hierarchical CAD approach was implemented.
• A simple, low-complexity model was used for initial circuit behavior prediction and candidate assessment via branch-and-bound.
• A complex, nonlinear model was employed for fine-grained search within a reduced solution space.

Main Results:

• The hierarchical approach demonstrated a significant speed-up of 3 orders of magnitude.
• Evaluated on 11 benchmark circuits and 102 experimental designs.
• Achieved comparable or improved accuracy compared to existing methods.

Conclusions:

• The proposed hierarchical CAD architecture efficiently addresses the computational challenges in biological design.
• This method significantly accelerates the design of reliable biological circuits.
• Offers a promising solution for advancing computer-aided biological engineering.