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Bioinformatics Advance Access published online on August 12, 2004
Bioinformatics, doi:10.1093/bioinformatics/bth474
Bioinformatics © Oxford University Press 2004; all rights reserved
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Received March 31, 2004
Revised June 16, 2004
Accepted August 7, 2004

Applications note

Microarray data mining with visual programming

Tomaz Curk 1, Janez Demsar 1, Qikai Xu 2, Gregor Leban 1, Uros Petrovic 3, Ivan Bratko 4, Gad Shaulsky 2, Blaz Zupan 5*

1 University of Ljubljana, Faculty of Computer and Information Science, Baylor College of Medicine, Houston, TX 77030, USA
2 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Graduate Program in Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, Houston, TX 77030, USA
3 Jozef Stefan Institute, Ljubljana, Slovenia, Baylor College of Medicine, Houston, TX 77030, USA
4 University of Ljubljana, Faculty of Computer and Information Science, Baylor College of Medicine, Houston, TX 77030, USA; Jozef Stefan Institute, Ljubljana, Slovenia, Baylor College of Medicine, Houston, TX 77030, USA
5 University of Ljubljana, Faculty of Computer and Information Science, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA

* To whom correspondence should be addressed. E-mail: blaz.zupan{at}fri.uni-lj.si.


  Abstract

Summary: Visual programming offers an intuitive means of combining known analysis and visualization methods into powerful applications. The system presented here enables users who are not programmers to manage microarray and genomic data flow and to customize their analysis by combining common data analysis tools to fit their needs.

Availability: http://www.ailab.si/supp/bi-visprog.

Supplementary information: http://www.ailab.si/supp/bi-visprog.


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