Evolving concurrent petri net models of epistasis

Michael Mayo, Lorenzo Beretta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A genetic algorithm is used to learn a non-deterministic Petri net-based model of non-linear gene interactions, or statistical epistasis. Petri nets are computational models of concurrent processes. However, often certain global assumptions (e.g. transition priorities) are required in order to convert a non-deterministic Petri net into a simpler deterministic model for easier analysis and evaluation. We show, by converting a Petri net into a set of state trees, that it is possible to both retain Petri net non-determinism (i.e. allowing local interactions only, thereby making the model more realistic), whilst also learning useful Petri nets with practical applications. Our Petri nets produce predictions of genetic disease risk assessments derived from clinical data that match with over 92% accuracy.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages166-175
Number of pages10
Volume5991 LNAI
EditionPART 2
DOIs
Publication statusPublished - 2010
Event2010 Asian Conference on Intelligent Information and Database Systems, ACIIDS 2010 - Hue City, Viet Nam
Duration: Mar 24 2010Mar 26 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5991 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other2010 Asian Conference on Intelligent Information and Database Systems, ACIIDS 2010
CountryViet Nam
CityHue City
Period3/24/103/26/10

Keywords

  • concurrency
  • digital ulcers
  • epistasis
  • genetic algorithm
  • Petri net
  • systemic schlerosis

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Mayo, M., & Beretta, L. (2010). Evolving concurrent petri net models of epistasis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 5991 LNAI, pp. 166-175). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5991 LNAI, No. PART 2). https://doi.org/10.1007/978-3-642-12101-2_18