  In this work, we propose a general inversion framework to non-uniquely invert
a very large class of ordinary differential equations (ODEs) into chemical
reaction networks. A thorough treatment of the relevant chemical reaction
network theory from the literature is given. Various simulation results are
provided to augment the selection procedure for the inverse framework, where a
previously known kineticization strategy is shown to be deterministically
excellent but undesirable in chemical simulations. The utility of the framework
is verified by simulating reaction network forms of meaningful ODE systems, and
their time series are analyzed. In particular, we provide simulations of
deterministic chaotic attractors whose newly discovered reaction networks are
non-equivalent with any existing chemical interpretations within the
literature, as well as presenting exemplary figures which may form a roadmap to
the successful biochemical implementation of the integration of ODE systems.
