title: [Research on gene expression data based on clustering/classification technology].
abstract: As the work of sequencing the genome of the human and many model organisms has been partially or fully finished, the "postgenomic era" has begun. Scientists are turning their focus toward identifying gene function from sequencing. Clustering technology, as one of the important tools of analyzing gene expression data and identifying gene function, has been used widely. In this paper we discuss main clustering technology about gene expression data at present, analyze their advantages and disadvantages, present the methods to solve the problems and give new approaches to study gene expression data.
authors.affiliation: School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Li
authors.forename: Xiang-Long
authors.initials: XL
authors.lastname: Tang
authors.forename: Ya-Dong
authors.initials: YD
authors.lastname: Wang
authors.forename: Xia
authors.initials: X
authors.lastname: Li
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D016571:Neural Networks, Computer; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*