The Reasoning Engine: A Satisfiability Modulo Theories-Based Framework for Reasoning About Discrete Biological Models

Boyan Yordanov, Sara Jane Dunn, Colin Gravill, Himanshu Arora, Hillel Kugler, Christoph M. Wintersteiger

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)1046-1058
Number of pages13
JournalJournal of Computational Biology
Volume30
Issue number9
DOIs
StatePublished - 1 Sep 2023

Keywords

  • Satisfiability Modulo Theories
  • formal reasoning
  • gene regulatory networks
  • interaction networks
  • synthesis

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Genetics
  • Molecular Biology
  • Computational Theory and Mathematics
  • Modelling and Simulation

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