Supervised inference of gene-regulatory networks

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@Article{To:2008:BMCb,
  author =       "Cuong C To and Jiri Vohradsky",
  title =        "Supervised inference of gene-regulatory networks",
  journal =      "BMC Bioinformatics",
  year =         "2008",
  volume =       "9",
  number =       "2",
  month =        jan # " 4",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1186/1471-2105-9-2",
  abstract =     "Background

                 Inference of protein interaction networks from various
                 sources of data has become an important topic of both
                 systems and computational biology. Here we present a
                 supervised approach to identification of gene
                 expression regulatory networks. Results

                 The method is based on a kernel approach accompanied
                 with genetic programming. As a data source, the method
                 uses gene expression time series for prediction of
                 interactions among regulatory proteins and their target
                 genes. The performance of the method was verified using
                 Saccharomyces cerevisiae cell cycle and DNA/RNA/protein
                 biosynthesis gene expression data. The results were
                 compared with independent data sources. Finally, a
                 prediction of novel interactions within yeast gene
                 expression circuits has been performed.
                 Conclusion

                 Results show that our algorithm gives, in most cases,
                 results identical with the independent experiments,
                 when compared with the YEASTRACT database. In several
                 cases our algorithm gives predictions of novel
                 interactions which have not been reported.",
  notes =        "PMID:",
}

Genetic Programming entries for Cuong Chieu To Jiri Vohradsky

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