This page contains supplemental material for the following paper submitted to Bioinformatics:
VizRank: Finding Informative Data Projections in Functional Genomics by Machine Learning
Gregor Leban, Ivan Bratko, Uros Petrovic, Tomaz Curk and Blaz Zupan
Abstract:
VizRank is a tool that finds interesting two-dimensional projections of class-labeled data. When applied to multi-dimensional functional genomics data sets, VizRank can systematically find relevant biological patterns.
Supplemental information is available for the following topics:
Installation, where you can download Orange, the data mining package that includes our implementation of VizRank for scatterplot and radviz visualizations.
Start with VizRank in Orange, where we show how to load the data and rank two-dimensional projections by VizRank in Orange.
VizRank method details, where we provide detailed description of the method for ranking of two-dimensional data projections.
Supported visualization methods, where we describe the visualization methods which are associated with VizRank in our implementation.
Comparison with other methods, where we shortly describe other visualization methods used by genetics and compare them to VizRank.
S. cerevisiae metabolic example, for which we show insightful projections that separate between three functional groups (respiration, cytoplasmic ribosomes and proteasome) from the data from study of Brown et al. (2000).
S. cerevisiae cell-cycle example, where we present
interesting data projections found by VizRank. The data used in this example is from the study by Spellman et al. (1998).
References:
Brown, M.P., Grundy, W.N., Lin, D., Cristianini, N., Sugnet, C., Furey, T.S., Ares, M., Haussler, D. (2000) Knowledge-based analysis of microarray gene expression data by using support vector machines, Proceedings of the National Academy of Sciences, 1 , 262�267.
Demsar, J., Zupan, B. (2004) Orange : From Experimental Machine Learning to Interactive Data Mining, A White Paper. AI Lab, Faculty of Computer and Information Science, Ljubljana.
DeRisi J, Iyer V, Brown P. (1997) Exploring the metabolic and genetic control of gene expression on a genomic scale. Science, 278 , 680--6.
McCarthy, J.F., Marx, K.A., Hoffman, P.E., Gee, A.G., O'Neil, P., Ujwal, M.L., Hotchkiss J. (2004) Applications of Machine Learning and High-Dimensional Visualization in Cancer Detection, Diagnosis, and Management, Annals of the New York Academy of Sciences, 1020 , 239�262.
Hoffman, P.E., Grinstein, G., Marx, K., Grosse, I., Stanley, E. (1997) DNA Visual and Analytic Data Mining, IEEE Visualization 1997, 1 , 437�441.