A Language for Modeling and Optimizing Experimental Biological Protocols

Automation is becoming ubiquitous in all laboratory activities, moving towards precisely defined and codified protocols. However, the integration between protocols mathematical models still lacking. Models describe physical processes, while define steps carried out during an experiment: neither cover domain of other, although they both attempt to characterize same phenomena. We should ideally start from integrated description model test it, concurrently analyze uncertainties parameters, equipment tolerances, data collection. To this end, we present a language optimize experimental biochemical that facilitates such description, can be combined with data. provide probabilistic semantics for our terms Gaussian processes (GPs) based on linear noise approximation (LNA) formally characterizes collection, underlying model, protocol operations. In set case studies, illustrate how resulting framework allows automated analysis optimization protocols, including Gibson assembly