Multicriteria global optimization for biocircuit design

TL;DR

This paper introduces a multiobjective optimization framework for designing complex biocircuits in synthetic biology, enabling systematic exploration of trade-offs between multiple design criteria.

Contribution

It presents a novel multiobjective formulation and optimization tool that handles high complexity in biocircuit design, surpassing traditional single-criterion approaches.

Findings

The method generates non-intuitive, functional biocircuit designs.

It effectively manages multiple competing design objectives.

The approach enables exploration of diverse design trade-offs.

Abstract

One of the challenges in Synthetic Biology is to design circuits with increasing levels of complexity. While circuits in Biology are complex and subject to natural tradeoffs, most synthetic circuits are simple in terms of the number of regulatory regions, and have been designed to meet a single design criterion. In this contribution we introduce a multiobjective formulation for the design of biocircuits. We set up the basis for an advanced optimization tool for the modular and systematic design of biocircuits capable of handling high levels of complexity and multiple design criteria. Our methodology combines the efficiency of global Mixed Integer Nonlinear Programming solvers with multiobjective optimization techniques. Through a number of examples we show the capability of the method to generate non intuitive designs with a desired functionality setting up a priori the desired level of complexity. The presence of more than one competing objective provides a realistic design setting where every design solution represents a trade-off between different criteria. The tool can be useful to explore and identify different design principles for synthetic gene circuits.