Cluster analysis and display of genome-wide expression patterns

Abstract

A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.

Keywords

GenomeGeneBiologyComputational biologySaccharomyces cerevisiaeCluster analysisGeneticsDNA microarrayFunction (biology)Gene expressionSimilarity (geometry)Gene clusterExpression (computer science)Microarray databasesHuman genomeComputer scienceArtificial intelligence

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Publication Info

Year: 1998
Type: article
Volume: 95
Issue: 25
Pages: 14863-14868
Citations: 16293
Access: Closed

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APA Style

                            
                                
                                    Michael B. Eisen, 
                                
                                    Paul T. Spellman, 
                                
                                    Patrick O. Brown
                                
                                et al.
                            
                            (1998). 
                            Cluster analysis and display of genome-wide expression patterns. 
                            Proceedings of the National Academy of Sciences
                            , 95
                            (25)
                            , 14863-14868.
                            https://doi.org/10.1073/pnas.95.25.14863
                        

Identifiers

DOI: 10.1073/pnas.95.25.14863