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Sixth International Conference on Computational Intelligence and Multimedia Applications (ICCIMA'05)
Applying Text Mining and Machine Learning Techniques to Gene Clusters Analysis
Las Vegas, Nevada
August 16-August 18
ISBN: 0-7695-2358-7
| ASCII Text | x | ||
| Debora Maria Rossi de Medeiros, André Carlos Ponce de Leon Ferreira de Carvalho, "Applying Text Mining and Machine Learning Techniques to Gene Clusters Analysis," Computational Intelligence and Multimedia Applications, International Conference on, pp. 23-28, Sixth International Conference on Computational Intelligence and Multimedia Applications (ICCIMA'05), 2005. | |||
| BibTex | x | ||
| @article{ 10.1109/ICCIMA.2005.12, author = {Debora Maria Rossi de Medeiros and André Carlos Ponce de Leon Ferreira de Carvalho}, title = {Applying Text Mining and Machine Learning Techniques to Gene Clusters Analysis}, journal ={Computational Intelligence and Multimedia Applications, International Conference on}, volume = {0}, year = {2005}, isbn = {0-7695-2358-7}, pages = {23-28}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICCIMA.2005.12}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Computational Intelligence and Multimedia Applications, International Conference on TI - Applying Text Mining and Machine Learning Techniques to Gene Clusters Analysis SN - 0-7695-2358-7 SP23 EP28 A1 - Debora Maria Rossi de Medeiros, A1 - André Carlos Ponce de Leon Ferreira de Carvalho, PY - 2005 KW - null VL - 0 JA - Computational Intelligence and Multimedia Applications, International Conference on ER - | |||
Genomic data clustering has been receiving a growing attention during last years. However, finding the biological meaning of the clusters is still a manual work, which becomes very difficult as the amount of data grows. In this paper, the authors present a few experiments applying Text Mining and Machine Learning techniques to help associating meaning to genes clusters. These experiments were applied to papers abstracts and interaction database data related to Saccaromyces cerevisiae genes both for identifying texts content and for explaining the biological meaning of the genes clusters found. The results were compared to information published by experts in molecular biology and a number of relevant equivalences were found.
Citation:
Debora Maria Rossi de Medeiros, André Carlos Ponce de Leon Ferreira de Carvalho, "Applying Text Mining and Machine Learning Techniques to Gene Clusters Analysis," iccima, pp.23-28, Sixth International Conference on Computational Intelligence and Multimedia Applications (ICCIMA'05), 2005
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