@inproceedings{muller_connecting_2009,
	title = {Connecting Genes with Diseases},
	doi = {10.1109/IV.2009.86},
	abstract = {This paper presents a visual data mining approach using the combination of clinical data, pathways and gene-expression data. The visual exploration of medical data using pathways to navigate and filter the data allows a more systematic and efficient investigation of problems in modern life science. A multiplicity of hypothesis can be evaluated in the same period of time, enabling a much better exploitation of the data. We present a system for data preprocessing and automatic classification, a set of visualization views and finally the integration in the Caleydo visualization framework, which enables the ldquocouplingrdquo of genetic and a broad spectrum of clinical data. With the help of the Caleydo framework the medical expert can identify connections between genetic parameters, patient subgroups, and drug responses.},
	booktitle = {Information Visualisation, 2009 13th International Conference},
	author = {Muller, H. and Reihs, R. and Sauer, S. and Zatloukal, K. and Streit, M. and Lex, A. and Schlegl, B. and Schmalstieg, D.},
	month = jul,
	year = {2009},
	keywords = {automatic classification, bioinformatics, biomolecular data, Caleydo visualization framework, clinical data, data mining, Data preprocessing, data visualisation, data visualization, diseases, drugs, Filters, gene expression, gene-expression data, genetic coupling, genetics, information visualization, Joining processes, medical administrative data processing, Medical diagnostic imaging, Medical Glyphs, parallel coordinates, Pathways, visual data mining approach},
	pages = {323--330}}