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Goal driven analysis of cDNA microarray data

  • Youlian Pan
  • , Jitao Zou
  • , Yi Huang
  • , Ziying Liu
  • , Sieu Phan
  • , Fazel A. Famili

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Microarray technology has been used extensively for high throughput gene expression studies. Many bioinformatics tools are available for analysis of microarray data. In the data mining process, it is important to be goal oriented so that a set of proper tools can be assembled for the targeted knowledge discovery process. In this paper, we tackle this issue by using a microarray dataset from Brassica endosperm together with EST data to validate our process. We were most interested in which genes are highly expressed in1 Brassica endosperm and their variations and functions over various stages in embryo development. We also performed gene characterization based on gene ontology analysis. Our results indicate that designing a specific data mining workflow that considers both the log ratio and signal intensity enhances knowledge discovery process. Through this approach, we were able to find the regulatory relationship between two most important transcription factors, LEC1 and WRI1 in the endosperm of Brassica napus.

Original languageEnglish (US)
Title of host publication2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings
Pages186-192
Number of pages7
DOIs
StatePublished - 2009
Event2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Nashville, TN, United States
Duration: Mar 30 2009Apr 2 2009

Publication series

Name2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009 - Proceedings

Other

Other2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2009
Country/TerritoryUnited States
CityNashville, TN
Period3/30/094/2/09

All Science Journal Classification (ASJC) codes

  • General Biochemistry, Genetics and Molecular Biology
  • Artificial Intelligence
  • Computational Theory and Mathematics

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