The general methodology used in artificial / synthetic biology research is the engineering approach of "design-build-test-learn". We here describe this methodology as it applies to the engineering of life-like systems.
Rational design of novel systems is central to explore novel life-like systems. Computer design enables us to create novel molecular systems that can later be synthesized and tested. The development of new machine-learning techniques allow biomolecules and genomes to be designed efficiently.
Synthesis of biomolecules, nanoparticles and materials is central to constructing life-like systems. Many of these synthesis methods are core expertise of laboratories at different departments at AU.
Experimental characterization of the synthesized systems is of central importance for understanding their properties. We use a wide variety of analytical instruments for the elucidation of nanostructures and functionalities at high resolution.
Finally, we compare the data to the original design and simulation of the system and hope to get surprised, since this is a sign that we have learned something new and leads to new design efforts and repeats of the "design-build-test-learn" cycle.
Here we list the methods and equipment most relevant for artificial biology research based on the expertise of individual research groups and on the lists of core facilities available at iNANO, Physics, Chemistry, Molecular Biology and Genetics, Biomedicine, and Clinical Medicine at Aarhus University.
