Skip to main content
SpringerLink
Log in

Web-Based Interface for the Visualization of Microarray Data

  • Conference paper
Advances in Visual Computing (ISVC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4291))

Included in the following conference series:

  • 1718 Accesses

Abstract

This paper presents the design and development of a web-based interface for the visualization of high dimensional data such as microarray data. A co-ordinate based method, namely, 3D Star Coordinate (3SC) projection technique is used for the visualization. The proposed web-based interface enables the user to choose an existing dataset from the database or upload a dataset and visualize the best possible projection of the data on an applet running on the client web browser. The proposed projection algorithm runs in Matlab at the server side for faster computation and using Java Servlets the results are delivered to the client machine.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Teoh, S.T., Ma, K.L.: PaintingClass: Interactive construction, Visualization and Exploration of Decision Trees. In: Proceedings of 9th ACM SIGKDD, pp. 667–672 (2003)

    Google Scholar 

  2. Stanford-biomedical-Informatics,Classification of Expression Arrays(CLEAVER), http://classify.stanford.edu

  3. Shaik, J., Kothari, C.R., Russomanno, D.J., Yeasin, M.: 3D Visualization of Relation Clusters from OWL Ontologies. In: Proceedings of SWWS 2006- The international conference on Semantic Web and Web Services (2006)

    Google Scholar 

  4. Shaik, J., Yeasin, M.: Visualization of High Dimensional Data using an Automated 3D Star Co-ordinate System. In: Proceedings of IEEE IJCNN 2006, Vancouver, Canada (2006)

    Google Scholar 

  5. Computer_Vision_Pattern_and_Image_Analysis_Lab, "3D Star Coordinate Based Web Application." Memphis, Tennessee (2005-2006), http://www.ee.memphis.edu/people/faculty/myeasin/CVPIA/Demo/index.htm

  6. Shaik, J., Yeasin, M.: Adaptive Ranking and Selection of Differentially Expressed Genes from Microarray Data. WSEAS transactions on Biology and Biomedicine 3, 125–133 (2006)

    Google Scholar 

  7. Shaik, J., Yeasin, M.: A Progressive Framework for Two-Way Clustering Using Adaptive Subspace Iteration for Functionally Classifying Genes. In: Proceedings of IEEE IJCNN 2006, Vancouver, Canada (2006)

    Google Scholar 

  8. Shaik, J., Yeasin, M.: Performance Evaluation of Subspace-based Algorithm in Selecting differentially Expressed Genes and Classification of Tissue Types from Microarray Data. In: Proceedings of IEEE IJCNN 2006, Vancouver, Canada (2006)

    Google Scholar 

  9. Bertin, J.: Graphics and Graphic Information Processing. Walter de Gruyer & Co, Berlin (1981)

    Google Scholar 

  10. Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York (1981)

    MATH  Google Scholar 

  11. Chernoff, H.: The Use of Faces to Represent Points in k-Dimensional Space Graphically. Journal of American Statistical Association 68, 361–368 (1971)

    Article  Google Scholar 

  12. Hoffman, P.E., Grinstein, G.G., Marx, K., Grosse, I.: DNA Visual and Analytic Datamining. In: IEEE visualization 1997, pp. 437–441 (1997)

    Google Scholar 

  13. Inselberg, A.: n-dimensional graphics, part I-lines and hyperplanes, IBM Scientific center, Los Angeles (1981)

    Google Scholar 

  14. Kandogan, E.: Star Coordinates: A multi-dimensional Visualization Technique with Uni-form treatment of Dimensions. In: Proceedings of IEEE information Visualization Symposium (2000)

    Google Scholar 

  15. National_Institute_of_Allergy_and_Infectious_Disease, Database for annotation and Visu-alization and Integrated discovery (David) Maryland, US, http://david.abcc.ncifcrf.gov

  16. Olsen, K.A., Korfhage, R.R., Sochats, K.M., Spring, M.B., Williams, J.G.: Visualization of Document Collection: The VIBE System. Information Processing and Management 29, 69–81 (1993)

    Article  Google Scholar 

  17. Pickett, R.M., Grinstein, G.G.: Iconographic Displays for Visualizing Multidimensional Data. In: IEEE conference on Systems, Man and Cybernetics, vol. 1, pp. 514–519 (1988)

    Google Scholar 

  18. Ridder, D., Kouropteva, O., Okun, O., Pietikainen, M., Duin, R.P.W.: Supervised Locally Linear embedding. In: International Conference on Artificial Neural Networks, pp. 333–341 (2003)

    Google Scholar 

  19. Integromics, Gene Engine. Madrid, Spain http://www.engene.cnb.uam.es

  20. Unsalan, C., Ercil, A.: Shapes of features and a modified measure for Linear Discriminant Analysis. In: OCPR 2000, vol. 2, pp. 410–413 (2000)

    Google Scholar 

  21. European_Bioinformatics_Institute, Expression Profiler, Cambridge, UK, http://www.ebi.ac.uk/expressionprofiler/

  22. National_Center_for_ontological_investigations, Gene Expression Pattern Analysis Suite (GEPAS). Madrid, Spain, http://bioinfo.cnio.es

  23. X-mine_Inc, X-Miner, http://www.x-mine.com

  24. Asimov, D.: The grand tour: a tool for viewing multidimensional data. SIAM Journal on Scientific and Statistical Computing 6, 128–143 (1985)

    Article  MATH  MathSciNet  Google Scholar 

  25. Beddow, J.: Shape coding of multidimensional data on microcomputer display. In: Proceedings of 1st international conference on Visualization 1990, Sanfransisco, california (1990)

    Google Scholar 

  26. Chernoff, H.: The Use of Faces to Represent Points in k-Dimensional Space Graphically. Journal of American Statistical Association 68, 361–368

    Google Scholar 

  27. Quinlan, R.: Combining Instance-Based and Model-Based Learning. In: Proceedings of tenth International conference of Machine Learning, pp. 236–243 (1993)

    Google Scholar 

  28. Fisher, R.A.: The use of multiple measurements in taxonomic problems. Annual Eugenics 7, 179–188 (1936)

    Google Scholar 

  29. Golub, T.R., Slonim, D.K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J.P., Coller, H., Loh, M.L., Downing, J.R., Caligiuri, M.A., Bloomfield, C.D., Lander, E.S.: Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286, 531–537 (1999)

    Article  Google Scholar 

  30. Makridakis, S., Wheelwright, S.C., Hyndman, R.J.: Forecasting:Methods and Applications. John Wiley and Sons, Chichester (1998)

    Google Scholar 

  31. Chen, X., Leung, S.Y., Yeuen, S.T., Chu, K.M., Ji, J., Li, R., Chan, A.S.Y., Law, S., Troyanskaya, O.G., Wong, J., So, S., Botstein, D., Brown, P.O.: Variation in Gene Expres-sion Patterns in Human Gastric Cancers. Mol. Bio. Cell 14, 3208–3215 (2003)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electrical and Computer Engineering, Computer Vision, Pattern and Image Analysis Lab, University of Memphis, Memphis, TN, 38152, USA

    B. Vanteru, J. Shaik & M. Yeasin

Authors
  1. B. Vanteru
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. Shaik
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. Yeasin
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Digital Image Research Center, Kingston University, London, UK

    Paolo Remagnino

  6. Intel, 95052, Santa Clara, CA, USA

    Ara Nefian

  7. University of California, 430, Computer Science Building, 92697-3425, Irvine, CA, USA

    Gopi Meenakshisundaram

  8. Institute for Data Analysis and Visualization, P.O. Box

    Valerio Pascucci

  9. Department of Computer Science and Engineering, Czech Technical University in Prague, Czech

    Jiri Zara

  10. Rockwell Scientific, 1049 Camino Dos Rios, 91360, Thousand Oaks, CA, USA

    Jose Molineros

  11. Computer Graphics Group, Bielefeld University, D-33501, Bielefeld, Germany

    Holger Theisel

  12. Hewlett Packard Labs, Palo Alto, CA, USA

    Tom Malzbender

Rights and permissions

Reprints and permissions

Copyright information

Âİ 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Vanteru, B., Shaik, J., Yeasin, M. (2006). Web-Based Interface for the Visualization of Microarray Data. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2006. Lecture Notes in Computer Science, vol 4291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11919476_81

Download citation

  • DOI: https://doi.org/10.1007/11919476_81

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-48628-2

  • Online ISBN: 978-3-540-48631-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation