A Parallel Approach to Perform Threshold Value and Propagation Delay Analyses of Genetic Logic Circuit Models

Sanaullah*, Hasan Baig, Jan Madsen, Jeong A. Lee*

*Corresponding author for this work

Research output: Contribution to journalJournal article

Abstract

Experiments with synthetic genetic logic circuits can be time-consuming and expensive. Accordingly, advances in the field of computer-aided design and simulation of genetic circuits have reduced the cost and time required for experimentation. D-VASim is the first genetic circuit simulation tool that allows users to interact with the model during run-time. In contrast to electronic circuits, genetic circuits have different threshold values for different circuits, which need to be estimated prior to simulation. D-VASim allows the user to perform threshold concentration and propagation delay analysis before simulating the circuit. The algorithm currently used in D-VASim has considerable scope for improvements. Thus, we propose a parallel implementation of the algorithm, significantly faster by up to 16 times. In adddition, we improve the algorithm for consistent runtimes across multiple simulation runs under the same parameter settings, reducing the worst-case standard deviation in runtime from 6.637 to 1.841. Our algorithm also estimates the threshold value more accurately, as evident from experimentation for long runtimes. With these modifications, the utility of D-VASim as a virtual laboratory environment has been significantly enhanced.

Original languageEnglish
JournalACS Synthetic Biology
Volume9
Pages (from-to)3422-3428
ISSN2161-5063
DOIs
Publication statusPublished - 2020

Keywords

  • Genetic logic circuits
  • Parallel programming LATEX
  • SBML
  • Stochastic simulation
  • Synthetic biology
  • Threshold value analysis
  • Timing analysis
  • Virtual instrumentation

Fingerprint Dive into the research topics of 'A Parallel Approach to Perform Threshold Value and Propagation Delay Analyses of Genetic Logic Circuit Models'. Together they form a unique fingerprint.

Cite this