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|
|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 noteOther page information: 825-829
Conference 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