Conceptual Clustering of Heterogeneous Gene Expression Sequences

摘要

We are concerned with clustering andcharacterising gene expression sequences thathave been classified according to heterogeneousclassification schemes. We adopt a model-basedapproach that uses a Hidden Markov Model (HMM)that has as states the stages of the underlyingprocess that generates the gene sequences, thusallowing us to handle complex and heterogeneousdata. Each cluster is described in terms of aHMM where we seek to find schema mappingsbetween the states of the original sequencesand the states of the HMM.