关键词: 聚类, 分子动理学, 互作用力, 基因表达, 数据挖掘, 知识发现

Abstract: In order to find possible diagnostic genes that may typically assist in disease diagnosis, clustering technologies are always used to analyze gene expression data. Molecular-kinetic-theory-based clustering approach is a new and effective clustering technique. It finds data clusters by following the molecular kinetic mechanism. This dynamic clustering approach does not require presetting the number of clusters and can be used to estimate the number of clusters. The authors applied the method on gene expression data to estimate the number of clusters and possible diagnostic genes according to relevant clustering criteria. The simulation results and analysis verify the good knowledge discovery ability of this approach.

Key words: clustering, molecular kinetics, interaction, gene expression, data mining, knowledge discovery