We propose a formal analysis approach aiming at featuring both expressiveness and ease of use. Its main ingredients are: i) a minimal notation to precisely represent bio-chemical interactions, and ii) an automated tool allowing the human expert to easily vary conditions of the in silico experiment. In particular, we exploit an analogy between logical implication and chemical reaction, i.e., roughly, the reaction of two molecules A and B producing a third one, C, can be interpreted as A and B logically imply C. Starting from a description of a metabolic network, in terms of reaction rules and initial conditions, chains of reactions, causally depending one from the another, can be mechanically deduced. Then, both the components of the initial state and, noticeably, the clauses ruling reactions can be changed and a new trial of the experiment started, according to a what-if investigation strategy. The method is supported by a computational logic counterpart, based on a Prolog implementation, which allows for a representation language closely correspondent to the adopted chemical abstract notation. The proposed framework has been validated by studying the robustness of the metabolic network of Escherichia coli K12. Selected genes have been knocked-out by disabling the rules regarding the encoded enzymes. Results are coherent with the actual biological behaviour.

A Toolkit Supporting Formal Reasoning about Causality in Metabolic Networks

BODEI, CHIARA;
2007-01-01

Abstract

We propose a formal analysis approach aiming at featuring both expressiveness and ease of use. Its main ingredients are: i) a minimal notation to precisely represent bio-chemical interactions, and ii) an automated tool allowing the human expert to easily vary conditions of the in silico experiment. In particular, we exploit an analogy between logical implication and chemical reaction, i.e., roughly, the reaction of two molecules A and B producing a third one, C, can be interpreted as A and B logically imply C. Starting from a description of a metabolic network, in terms of reaction rules and initial conditions, chains of reactions, causally depending one from the another, can be mechanically deduced. Then, both the components of the initial state and, noticeably, the clauses ruling reactions can be changed and a new trial of the experiment started, according to a what-if investigation strategy. The method is supported by a computational logic counterpart, based on a Prolog implementation, which allows for a representation language closely correspondent to the adopted chemical abstract notation. The proposed framework has been validated by studying the robustness of the metabolic network of Escherichia coli K12. Selected genes have been knocked-out by disabling the rules regarding the encoded enzymes. Results are coherent with the actual biological behaviour.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/112830
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