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Citation
Dougherty, J., Tabus, I., Astola, J. (2008). Inference of gene regulatory networks based on a universal minimum description length.  EURASIP J. Bioinform. Syst. Biol. (): 482090.
FlyBase ID
FBrf0204773
Publication Type
Research paper
Abstract

The Boolean network paradigm is a simple and effective way to interpret genomic systems, but discovering the structure of these networks remains a difficult task. The minimum description length (MDL) principle has already been used for inferring genetic regulatory networks from time-series expression data and has proven useful for recovering the directed connections in Boolean networks. However, the existing method uses an ad hoc measure of description length that necessitates a tuning parameter for artificially balancing the model and error costs and, as a result, directly conflicts with the MDL principle's implied universality. In order to surpass this difficulty, we propose a novel MDL-based method in which the description length is a theoretical measure derived from a universal normalized maximum likelihood model. The search space is reduced by applying an implementable analogue of Kolmogorov's structure function. The performance of the proposed method is demonstrated on random synthetic networks, for which it is shown to improve upon previously published network inference algorithms with respect to both speed and accuracy. Finally, it is applied to time-series Drosophila gene expression measurements.

PubMed ID
PubMed Central ID
PMC3171396 (PMC) (EuropePMC)
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Secondary IDs
    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    EURASIP J. Bioinform. Syst. Biol.
    Title
    EURASIP Journal on Bioinformatics and Systems Biology
    ISBN/ISSN
    1687-4153 1687-4145
    Data From Reference
    Genes (20)