LiU Electronic Press
Full-text not available in DiVA
Author:
Doherty, Patrick (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab) (Linköping University, The Institute of Technology)
Kertes, Steven (Stanford University)
Magnusson, Martin (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab) (Linköping University, The Institute of Technology)
Szalas, Andrzej (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab) (Linköping University, The Institute of Technology)
Title:
Towards a logical analysis of biochemical pathways
Department:
Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab
Linköping University, The Institute of Technology
Publication type:
Conference paper (Refereed)
Language:
English
In:
Proceedings of the 9th European Conference on Logics in Artificial Intelligence (JELIA)
Editor:
José Júlio Alferes and João Alexandre Leite
Conference:
European Conference on Logics in Artificial Intelligence JELIA2004, 2004
Publisher: Springer
Series:
Lecture Notes in Computer Science, ISSN 0302-9743; 3229
Volume:
3229
Pages:
667-679
Year of publ.:
2004
URI:
urn:nbn:se:liu:diva-48268
Permanent link:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-48268
ISBN:
978-3-540-23242-1
Subject category:
Engineering and Technology
SVEP category:
TECHNOLOGY
Keywords(en) :
abduction, biochemical pathways, hypotheses generation, weakest sufficient and strongest necessary conditions
Abstract(en) :

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.

Available from:
2009-10-11
Created:
2009-10-11
Last updated:
2012-01-18
Statistics:
40 hits