Argumentation to represent and reason over biological systems

Adam Wyner*, Luke Riley, Robert Hoehndorf, Samuel Croset

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


In systems biology, networks represent components of biological systems and their interactions. It is a challenge to efficiently represent, integrate and analyse the wealth of information that is now being created in biology, where issues concerning consistency arise. As well, the information offers novel methods to explain and explore biological phenomena. To represent and reason with inconsistency as well as provide explanation, we represent a fragment of a biological system and its interactions in terms of a computational model of argument and argumentation schemes. Process pathways are represented in terms of an argumentation scheme, then abstracted into a computational model for evaluation, yielding sets of 'consistent' arguments that represent compatible biological processes. From the arguments, we can extract the corresponding processes. We show how the analysis supports explanation and systematic exploration in a biology network.

Original languageEnglish (US)
Title of host publicationInformation Technology in Bio- and Medical Informatics - Third International Conference, ITBAM 2012, Proceedings
Number of pages15
StatePublished - 2012
Externally publishedYes
Event3rd International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2012 - Vienna, Austria
Duration: Sep 4 2012Sep 5 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7451 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other3rd International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2012


  • argumentation
  • computational methods
  • systems biology

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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