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.",
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