  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.
