FAST: A simulation framework for solving large-scale probabilistic inverse problems in nano-biomolecular circuits

Inverse problems in nano-biomolecular circuits typically involve stochastic functional elements that admit non-linear relationships between different circuit variables. In this regard, a factor graph representation serves as an important visualization and analysis tool that can be used to compute inferences over an arbitrary large-scale biomolecular circuit. Solving the inverse problem using a factor graph entails passing of messages/signals between the internal nodes of the biomolecular circuit, and the steady-state distribution of the messages can be used to determine the dynamics of the circuit and the final solution. In this paper, we present an open-source simulation tool that we have developed which can be used to verify the functionality of a generic nano-biomolecular circuit. As a representative example, we apply the simulation software to estimate the reliability of a 10³ size biosensor array where each element of the array is comprised of our previously reported antigen-antibody based biomolecular circuit. This example will demonstrate the utility of the proposed software in emulating the functionality of micro and nano biosensor arrays without resorting to time-consuming and laborious fabrication procedure and laboratory experiments.