A nonmonotonic logical approach for modelling and revising metabolic networks

Oliver Ray; Ken Whelan; Ross King

doi:10.1109/CISIS.2009.175

A nonmonotonic logical approach for modelling and revising metabolic networks

Oliver Ray, Ken Whelan, Ross King

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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 enzymecomplexes 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-ofthe- art model of Aromatic Amino Acid biosynthesis. © 2009 IEEE.

Original language	English
Title of host publication	Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009\|Proc. Int. Conf. Complex, Intell. Softw. Intensive Syst., CISIS
Pages	825-829
Number of pages	4
DOIs	https://doi.org/10.1109/CISIS.2009.175
Publication status	Published - 2009
Event	International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009 - Fukuoka Duration: 1 Jul 2009 → …

Conference

Conference	International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009
City	Fukuoka
Period	1/07/09 → …

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10.1109/CISIS.2009.175

Cite this

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title = "A nonmonotonic logical approach for modelling and revising metabolic networks",

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 enzymecomplexes 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-ofthe- art model of Aromatic Amino Acid biosynthesis. {\textcopyright} 2009 IEEE.",

author = "Oliver Ray and Ken Whelan and Ross King",

year = "2009",

doi = "10.1109/CISIS.2009.175",

language = "English",

isbn = "9780769535753",

pages = "825--829",

booktitle = "Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009|Proc. Int. Conf. Complex, Intell. Softw. Intensive Syst., CISIS",

note = "International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009 ; Conference date: 01-07-2009",

}

Ray, O, Whelan, K & King, R 2009, A nonmonotonic logical approach for modelling and revising metabolic networks. in Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009|Proc. Int. Conf. Complex, Intell. Softw. Intensive Syst., CISIS. pp. 825-829, International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009, Fukuoka, 1/07/09. https://doi.org/10.1109/CISIS.2009.175

A nonmonotonic logical approach for modelling and revising metabolic networks. / Ray, Oliver; Whelan, Ken; King, Ross.
Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009|Proc. Int. Conf. Complex, Intell. Softw. Intensive Syst., CISIS. 2009. p. 825-829.

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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AB - 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 enzymecomplexes 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-ofthe- art model of Aromatic Amino Acid biosynthesis. © 2009 IEEE.

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DO - 10.1109/CISIS.2009.175

M3 - Conference contribution

SN - 9780769535753

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BT - Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009|Proc. Int. Conf. Complex, Intell. Softw. Intensive Syst., CISIS

T2 - International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009

Y2 - 1 July 2009

ER -

A nonmonotonic logical approach for modelling and revising metabolic networks

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