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BMC Bioinformatics 2008
Using a logical model to predict the growth of yeastAbstract: Compared to the FBA model, the logical model has information on an additional 263 putative genes and 247 additional reactions. The correctness of this model was evaluated by comparison with iND750 (an updated FBA model closely related to iFF708) by evaluating the performance of both models on predicting empirical minimal medium growth data/essential gene listings.ROC analysis and other statistical studies revealed that use of the simpler logical form and larger coverage results in no significant degradation of performance compared to iND750.This paper describes the construction and application of a logical model of known metabolic processes in bakers' yeast (Saccharomyces cerevisiae). The model outlines the relationships between Open Reading Frames (ORFs), enzymes and reactions comprising the metabolic pathways in yeast, presenting the knowledge as facts in a restricted form of First Order Logic (FOL). This representation allows the model to behave as a deductive (or relational) database, as well as a model for the study of metabolic behaviour.A focus of our previous research has been the development and implementation of an automated system for the design, execution and interpretation of wet lab auxotrophic experiments: the Robot Scientist [1,2]. In its first incarnation the scope of the Robot Scientist was limited to rediscovery of knowledge from a single metabolic pathway in yeast (the Aromatic Amino Acid (AAA) biosynthesis pathway), where a logical model of this pathway [3] acted as background knowledge from which the Robot Scientist was able to generate hypotheses. The logical model presented here, "aber", is an updated and expanded version of this limited model (the name is derived from "Aberystwyth" – where the model was constructed). The model has been expanded to include most of what is known about yeast metabolism. The model has also been updated to a more explicitly relational data structure; replacing the single relation that included enzyme and metaboli
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