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 language | English |
|---|---|
| Pages (from-to) | 1046-1058 |
| Number of pages | 13 |
| Journal | Journal of Computational Biology |
| Volume | 30 |
| Issue number | 9 |
| DOIs | |
| State | Published - 1 Sep 2023 |
Bibliographical note
Publisher Copyright:© Mary Ann Liebert, Inc.
Funding
H.K.'s research was supported by the Horizon 2020 research and innovation program for the Bio4Comp project under grant agreement no. 732482 and by the Israel Science Foundation (grant no. 190/19).
| Funders | Funder number |
|---|---|
| Israel Science Foundation | 190/19 |
| Horizon 2020 | 732482 |
Keywords
- Satisfiability Modulo Theories
- formal reasoning
- gene regulatory networks
- interaction networks
- synthesis