Interactive visualization of clusters in microarray data: an efficient tool for improved metabolic analysis of E. coli.

ABSTRACT:

Background

Interpretation of comprehensive DNA microarray data sets is a challenging task for biologists and process engineers where scientific assistance of statistics and bioinformatics is essential. Interdisciplinary cooperation and concerted development of software-tools for simplified and accelerated data analysis and interpretation is the key to overcome the bottleneck in data-analysis workflows. This approach is exemplified by gcExplorer an interactive visualization toolbox based on cluster analysis. Clustering is an important tool in gene expression data analysis to find groups of co-expressed genes which can finally suggest functional pathways and interactions between genes. The visualization of gene clusters gives practitioners an understanding of the cluster structure of

SUBMITTER: Scharl T 

PROVIDER: S-EPMC2717919 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature