A Clustering System for Gene Expression Data Based upon Genetic Programming and the HS-Model

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Liu:2010:CSO,
  author =       "Guiquan Liu and Xiufang Jiang and Lingyun Wen",
  title =        "A Clustering System for Gene Expression Data Based
                 upon Genetic Programming and the HS-Model",
  booktitle =    "Third International Joint Conference on Computational
                 Science and Optimization (CSO)",
  year =         "2010",
  month =        "28-31 " # may,
  volume =       "1",
  pages =        "238--241",
  abstract =     "Cluster analysis is a major method to study gene
                 function and gene regulation information for there is a
                 lack of prior knowledge for gene data. Many clustering
                 methods existed at present usually need manual
                 operations or pre-determined parameters, which are
                 difficult for gene data. Besides, gene data possess
                 their own characteristics, such as large scale,
                 high-dimension, and noise. Therefore, a systematic
                 clustering algorithm should be proposed to effectively
                 deal with gene data. In this paper, a novel genetic
                 programming (GP) clustering system for gene data based
                 on hierarchical statistical model (HS-model) is
                 proposed. And an appropriate fitness function is also
                 proposed in this system. This clustering system can
                 largely eliminate the infection of data scale and
                 dimension. The proposed GP clustering system is applied
                 to cluster the whole intact yeast gene data without
                 dimensionality reduction. The experimental results
                 indicate that the algorithm is highly efficient and can
                 effectively deal with missing values in gene dataset.",
  keywords =     "genetic algorithms, genetic programming, hierarchical
                 statistical",
  DOI =          "doi:10.1109/CSO.2010.116",
  notes =        "Key Laboratory of Software in Computing and
                 Communication, Anhui Province School of Computer
                 Science and Technology University of Science and
                 Technology of China, Hefei, Anhui 230027, China

                 Also known as \cite{5532998}",
}

Genetic Programming entries for Guiquan Liu Xiufang Jiang Lingyun Wen

Citations