Abstract—Microarray technologies that monitor the level of expression of a large number of genes have emerged. And given the technology in deoxyribonucleic acid (DNA) - microarray data for a set of cells characterized by a phenotype an important problem is to identify “patterns” of gene expression that can be used to predict cell phenotype. The potential number of such patterns is exponential in the number of genes. Detection of genes biological function in silico which has not yet been discovered through other means aside from wet laboratories is of practical significance. In this research, biological function distribution of budding yeast cell Saccharomyces cerevisiae, using 170 classified gene expression data of yeast is used for visualization and analysis, and evaluated with the reference time distribution using FACS and budding index analysis. We define the criteria using edit distances, a good scientific visualization with 83.78% prediction on time series distribution on the first peak and 86.49% on the second peak.
Index Terms—DNA microarrays, gene expression, computational biology, saccharomyces cerevisiae, FACS, budding index analysis
Cite: Julie Ann A. Salido and Stephanie S. Pimentel, "Estimating Biological Function Distribution of Yeast Using Gene Expression Data," Journal of Image and Graphics, Vol. 2, No. 2, 158-163, December 2014. doi: 10.12720/joig.2.2.158-163
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