PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Visualizing Gene Interaction Graphs with Local Multidimensional Scaling
Jarkko Venna and Samuel Kaski
Proceedings of the 14th European Symposium on Artificial Neural Networks (ESANN'2006) pp. 557-562, 2006.

Abstract

Several bioinformatics data sets are naturally represented as graphs, for instance gene regulation, metabolic pathways, and protein-protein interactions. The graphs are often large and complex, and their straightforward visualizations are incomprehensible. We have recently developed a new method called \emph{local multidimensional scaling} for visualizing high-dimensional data sets. In this paper we adapt it to visualize graphs, and compare it with two commonly used graph visualization packages in visualizing yeast gene interaction graphs. The new method outperforms the alternatives in two crucial respects: It produces graph layouts that are both more trustworthy and have fever edge crossings.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:2537
Deposited By:Jarkko Venna
Deposited On:22 November 2006