Local multidimensional scaling

Several bioinformatics data sets are naturally represented as graphs, for instance gene regulation, metabolic pathways, and proteinprotein interactions. The graphs are often large and complex, and their straightforward visualizations are incomprehensible. We have recently developed a new method called 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.

• Type: Journal
• Year: 2006
• Where: NN
• Authors: Jarkko Venna, Samuel Kaski
• Keywords: Data Sets, Instance Gene Regulation, Neural Networks, NN 2006, Several Bioinformatics Data