Abstract
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.
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Doherty, P., Kertes, S., Magnusson, M., Szalas, A. (2004). Towards a Logical Analysis of Biochemical Pathways. In: Alferes, J.J., Leite, J. (eds) Logics in Artificial Intelligence. JELIA 2004. Lecture Notes in Computer Science(), vol 3229. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30227-8_55
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DOI: https://doi.org/10.1007/978-3-540-30227-8_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23242-1
Online ISBN: 978-3-540-30227-8
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