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Adapting Genetic Regulatory Models by Genetic Programming
University of Skövde, School of Humanities and Informatics.
University of Skövde, School of Humanities and Informatics.
2004 (English)In: Biosystems (Amsterdam. Print), ISSN 0303-2647, E-ISSN 1872-8324, Vol. 76, no 1-3, 217-227 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, we focus on the task of adapting genetic regulatory models based on gene expression data from microarrays. Our approach aims at automatic revision of qualitative regulatory models to improve their fit to expression data. We describe a type of regulatory model designed for this purpose, a method for predicting the quality of such models, and a method for adapting the models by means of genetic programming. We also report experimental results highlighting the ability of the methods to infer models on a number of artificial data sets. In closing, we contrast our results with those of alternative methods, after which we give some suggestions for future work.

Place, publisher, year, edition, pages
Elsevier, 2004. Vol. 76, no 1-3, 217-227 p.
Keyword [en]
Gene networks, Evolutionary algorithms, Machine learning
Identifiers
URN: urn:nbn:se:his:diva-1496DOI: 10.1016/j.biosystems.2004.05.014ISI: 000224134800022PubMedID: 15351145Scopus ID: 2-s2.0-4444303303OAI: oai:DiVA.org:his-1496DiVA: diva2:31772
Available from: 2007-07-02 Created: 2007-07-02 Last updated: 2014-08-19Bibliographically approved

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