Abstract
This paper describes a new logic-based approach for representing and reasoning about metabolic networks.
First it shows how biological pathways can be elegantly represented in a logic programming formalism
able to model full chemical reactions with substrates and products in different cell compartments,
and which are catalysed by iso-enzymes or enzyme-complexes that are subject to inhibitory feedbacks.
Then it shows how a nonmonotonic reasoning system called XHAIL can be used as a practical
method for learning and revising such metabolic networks from observational data.
Preliminary results are described in which the approach is validated
on a state-of-the-art model of Aromatic Amino Acid biosynthesis.
| Translated title of the contribution | A nonmonotonic logical approach for modelling and revising metabolic networks |
|---|---|
| Original language | English |
| Title of host publication | 3rd International Conference on Complex, Intelligent and Software Intensive Systems (from 2nd International Workshop on Intelligent Informatics in Biology and Medicine) |
| Publisher | IEEE Computer Society |
| Publication status | Published - 2009 |
Bibliographical note
Other page information: 825-829Conference Proceedings/Title of Journal: 3rd International Conference on Complex, Intelligent and Software Intensive Systems (from 2nd International Workshop on Intelligent Informatics in Biology and Medicine)
Other identifier: 2001003
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