The evolution of higher-level biochemical reaction models

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@Article{Ross:2011:GPEM,

• author = "Brian J. Ross",
• title = "The evolution of higher-level biochemical reaction models",
• journal = "Genetic Programming and Evolvable Machines",
• year = "2012",
• volume = "13",
• number = "1",
• pages = "3--31",
• month = mar,
• note = "Special Section on Evolutionary Algorithms for Data Mining",
• keywords = "genetic algorithms, genetic programming, Grammar-guided, Biochemical modelling, Time series, Statistical features, Process algebra",
• ISSN = "1389-2576",
• DOI = "doi:10.1007/s10710-011-9144-3",
• size = "29 pages",
• abstract = "Computational tools for analysing biochemical phenomena are becoming increasingly important. Recently, high-level formal languages for modeling and simulating biochemical reactions have been proposed. These languages make the formal mode ling of complex reactions accessible to domain specialists outside of theoretical computer science. This research explores the use of genetic programming to automate the construction of models written in one such language. Given a description of desired time-course data, the goal is for genetic programming to construct a model that might generate the data. The language investigated is Kahramanogullari's and Cardelli's Programming Interface for Modelling (PIM) language. The PIM syntax is defined in a grammar-guided genetic programming system. All time series generated during simulations are described by statistical feature tests, and the fitness evaluation compares feature proximity between the target and candidate solutions. PIM models of varying complexity were used as target expressions for genetic programming, and were successfully reconstructed in all cases. This shows that the compositional nature of PIM models is amenable to genetic program search.",
• affiliation = "Department of Computer Science, Brock University, 500 Glenridge Ave., St. Catharines, ON L2S 3A1, Canada",
• notes = "DCTG-GP written in Prolog. No genetic repair. MOGP (3 objectives: Mean, sd and skew) selection \cite{Bentley97}. Phagocytosis. All individuals unique (not equivalent to all models (phenotypes) being unique. PIM and SPiM written in OCAML.",

}

Genetic Programming entries for Brian J Ross

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