License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.DNA.2020.4
URN: urn:nbn:de:0030-drops-129574
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/12957/
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Vasic, Marko ; Soloveichik, David ; Khurshid, Sarfraz

CRNs Exposed: A Method for the Systematic Exploration of Chemical Reaction Networks

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LIPIcs-DNA-2020-4.pdf (0.6 MB)

Abstract

Formal methods have enabled breakthroughs in many fields, such as in hardware verification, machine learning and biological systems. The key object of interest in systems biology, synthetic biology, and molecular programming is chemical reaction networks (CRNs) which formalizes coupled chemical reactions in a well-mixed solution. CRNs are pivotal for our understanding of biological regulatory and metabolic networks, as well as for programming engineered molecular behavior. Although it is clear that small CRNs are capable of complex dynamics and computational behavior, it remains difficult to explore the space of CRNs in search for desired functionality. We use Alloy, a tool for expressing structural constraints and behavior in software systems, to enumerate CRNs with declaratively specified properties. We show how this framework can enumerate CRNs with a variety of structural constraints including biologically motivated catalytic networks and metabolic networks, and seesaw networks motivated by DNA nanotechnology. We also use the framework to explore analog function computation in rate-independent CRNs. By computing the desired output value with stoichiometry rather than with reaction rates (in the sense that X → Y+Y computes multiplication by 2), such CRNs are completely robust to the choice of reaction rates or rate law. We find the smallest CRNs computing the max, minmax, abs and ReLU (rectified linear unit) functions in a natural subclass of rate-independent CRNs where rate-independence follows from structural network properties.

BibTeX - Entry

@InProceedings{vasic_et_al:LIPIcs:2020:12957,
  author =	{Marko Vasic and David Soloveichik and Sarfraz Khurshid},
  title =	{{CRNs Exposed: A Method for the Systematic Exploration of Chemical Reaction Networks}},
  booktitle =	{26th International Conference on DNA Computing and Molecular Programming (DNA 26)},
  pages =	{4:1--4:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-163-4},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{174},
  editor =	{Cody Geary and Matthew J. Patitz},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/12957},
  URN =		{urn:nbn:de:0030-drops-129574},
  doi =		{10.4230/LIPIcs.DNA.2020.4},
  annote =	{Keywords: molecular programming, formal methods}
}

Keywords: molecular programming, formal methods
Collection: 26th International Conference on DNA Computing and Molecular Programming (DNA 26)
Issue Date: 2020
Date of publication: 04.09.2020
Supplementary Material: We release the source code of our tool at https://github.com/marko-vasic/crnsExposed to enable others make use of it, and extend it further.

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