Beyond clustering of array expressions
by Raja Loganantharaj
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 5, No. 3, 2009

Abstract: Microarray technology provides an opportunity to view transcriptions at genomic level under different experimental conditions. Generally, co-expressed genes, which are members of the same cluster, are expected to have similar function, but unfortunately it is not true due to various reasons including co-expression does not necessarily imply co-regulation. To improve the results of clustering, we investigate a method based on singular value decomposition (SVD) for integrating diverse data sources. We also introduce a new cluster evaluation method based on mutual information. Using time series data sets on yeast, we have empirically demonstrated the effectiveness of SVD as a data integrator.

Online publication date: Thu, 11-Jun-2009

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