In this particular study, we compared the global gene expression values from two nearly identical cell lines except the presence or absence of the transcription factor MTF-1. The goal is to identify MTF-1 mediated gene expressions after cadmium treatment. The initial data pre-processing steps include data transformation and normalization. The normalized data were then filtered and the remaining data were clustered using five clustering algorithms. The clustering results were evaluated on their sensitivity in detecting patterns and on their power of prediction. Our results suggest that the model based clustering offered a better approach than the hierarchical clustering. Furthermore, the Bayesian infinite mixture model based clustering showed the best gene expression patterns that were relevant to biological findings. Two groups of genes were identified to be either up- or down-regulated through MTF-1 in response to Cadmium. Such information will provide further insights in characterizing the function of this transcription factor.
|School:||University of Cincinnati|
|Department:||Environmental Health Sciences|
|School Location:||United States -- Ohio|
|Source:||MAI 57/06M(E), Masters Abstracts International|
|Keywords:||Cadmium, Clustering, Metal-response element-binding transcription factor-1, Microarrays|
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