Incorporating Gene Ontology in Clustering Gene Expression Data

In this paper we consider a general framework for clustering expression data that permits integration of various biological data sources through combination of corresponding dissimilarity measures. In the paper we briefly review currently published attempts to genomic data fusion and discuss a problem of validating results from clustering expression data. We apply our approach to a real microarray expression dataset which induces a correlationbased dissimilarity matrix, and use Gene Ontology

• Type: Conference
• Year: 2006
• Where: CBMS
• Authors: Rafal Kustra, Adam Zagdanski
• Keywords: Biological Data Sources, CBMS 2006, Expression Data, Genomic Data Fusion, Medical Imaging