Visualization of Gene Expression Data

 

 

 

 

 

 

 

 

 

Non Metric Multidimensional Scaling and Vector Fusion Visualization of Cell Cycle Independent Gene Expressions for Gene Function Analysis

Jhoirene Clemente {jhoiclemente@gmail.com} and Julie An Salido {julieansalido2@gmail.com}

Algorithms and Complexity Lab, Department of Computer Science

University of the Philippines Diliman, Quezon City, Philippines

 

Abstract

Numerous biological changes are associated to cell-cycle, making it an attractive model for the genomewide regulation of gene-activity. However, not all genes in human and in yeast have known functions, therefore analysis of gene expression data is widely studied in the literature for gene function discovery. In this paper the goal is to provide visualizations for gene expression analysis of cell-cycle specific genes in yeast. We define a set of qualitative criterion to assess the quality of the visualization result using Non-metric Multidimensional Scaling and Vector Fusion. As part of our intracluster evaluation, we define outlier genes based from the ellipse confidence interval with 95% confidence level. We inspect the set of genes and provide a table summarizing its membership with respect to its function.

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This paper is published in the 2010 National Conference of Information Technology Educators(NCITE) held last Oct in La Carmela De Boracay, Philippines

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