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  Indian J Med Microbiol
 

Figure 1: Bottom–up approach for analysis of gene expression profiles (GEPs): Clustering algorithms always produces a classification irrespective of biological relevance of produced clusters. The bottom–up approach tries to ensure the biological relevance of produced clusters by using gene-sets having highest probability of obtaining relevant clusters. The bottom–up approach assumes the gene-set a priori and applies it on GEPs using a classifier to obtain sample classification. The steps are followed in reverse order to the usual method of GEPs analysis.

Figure 1: Bottom–up approach for analysis of gene expression profiles (GEPs): Clustering algorithms always produces a classification irrespective of biological relevance of produced clusters. The bottom–up approach tries to ensure the biological relevance of produced clusters by using gene-sets having highest probability of obtaining relevant clusters. The bottom–up approach assumes the gene-set <i>a priori</i> and applies it on GEPs using a classifier to obtain sample classification. The steps are followed in reverse order to the usual method of GEPs analysis.