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GEA: a toolkit for gene expression analysis

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Published:03 June 2002Publication History

ABSTRACT

Currently gene expression data are being produced at a phenomenal rate. The general objective is to try to gain a better understanding of the functions of cellular tissues. In particular, one specific goal is to relate gene expression to cancer diagnosis, prognosis and treatment. However, a key obstacle is that the availability of analysis tools or lack thereof, impedes the use of the data, making it difficult for cancer researchers to perform analysis efficiently and effectively.

References

  1. R. Ng, J. Sander and M. Sleumer. Hierarchical cluster analysis of SAGE data for cancer profiling. BIOKDD Workshop on Data Mining in Bioinformatics, August 2001.Google ScholarGoogle Scholar
  2. T. Johnson, L. Lakshmanan and R. Ng. The 3W Model and algebra for Unified Data Mining. VLDB 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. GEA: a toolkit for gene expression analysis

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              cover image ACM Conferences
              SIGMOD '02: Proceedings of the 2002 ACM SIGMOD international conference on Management of data
              June 2002
              654 pages
              ISBN:1581134975
              DOI:10.1145/564691

              Copyright © 2002 ACM

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              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 3 June 2002

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