Doherty, Patrick Kertes, Steven Magnusson, Martin Szalas, Andrzej 2004 (English)In: Proceedings of the 9th European Conference on Logics in Artificial Intelligence (JELIA) / [ed] José Júlio Alferes and João Alexandre Leite, Springer, 2004, Vol. 3229, 667-679Conference paper (Refereed)
Biochemical pathways or networks are generic representations used to model many different types of complex functional and physical interactions in biological systems. Models based on experimental results are often incomplete, e.g., reactions may be missing and only some products are observed. In such cases, one would like to reason about incomplete network representations and propose candidate hypotheses, which when represented as additional reactions, substrates, products, would complete the network and provide causal explanations for the existing observations. In this paper, we provide a logical model of biochemical pathways and show how abductive hypothesis generation may be used to provide additional information about incomplete pathways. Hypothesis generation is achieved using weakest and strongest necessary conditions which represent these incomplete biochemical pathways and explain observations about the functional and physical interactions being modeled. The techniques are demonstrated using metabolism and molecular synthesis examples.
Lecture Notes in Computer Science, ISSN 0302-9743 ; 3229
abduction, biochemical pathways, hypotheses generation, weakest sufficient and strongest necessary conditions
National CategoryEngineering and Technology
Identifiersurn:nbn:se:liu:diva-48268 (URN)10.1007/978-3-540-30227-8_55 (DOI)978-3-540-23242-1 (ISBN)oai:DiVA.org:liu-48268 (OAI)diva2:269164 (DiVA)
European Conference on Logics in Artificial Intelligence JELIA2004, 2004