Yordanov Boyan, Dunn Sara-Jane, Gravill Colin, Arora Himanshu, Kugler Hillel, Wintersteiger Christoph M
Scientific Technologies, London, United Kingdom.
Microsoft Research, Cambridge, United Kingdom.
J Comput Biol. 2023 Sep;30(9):1046-1058. doi: 10.1089/cmb.2023.0117.
We present a framework called the Reasoning Engine, which implements Satisfiability Modulo Theories (SMT)-based methods within a unified computational environment to address diverse biological analysis problems. The Reasoning Engine was used to reproduce results from key scientific studies, as well as supporting new research in stem cell biology. The framework utilizes an intermediate language for encoding partially specified discrete dynamical systems, which bridges the gap between high-level domain-specific languages and low-level SMT solvers. We provide this framework as open source together with various biological case studies, illustrating the synthesis, enumeration, optimization, and reasoning over models consistent with experimental observations to reveal novel biological insights.
