Goal Driven Analysis of cDNA Microarray Data

Download
  1. (PDF, 800 KB)
AuthorSearch for: ; Search for: ; Search for: ; Search for: ; Search for: ; Search for:
TypeArticle
Proceedings titleProceedings of the 6th Annual IEEE conference on Computational Intelligence in Bioinformatics and Computational Biology
ConferenceIEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, Nashville, TN., USA, March 30 - April 02, 2009
ISBN978-1-4244-2756-7
Pages186192; # of pages: 7
SubjectMicroarray data analysis; gene expression; differentially expressed genes; transcriptional regulation
AbstractMicroarray 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 in 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.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada (NRC-CNRC); NRC Institute for Information Technology; NRC Plant Biotechnology Institute
Peer reviewedYes
NRC number50745
NPARC number16488512
Export citationExport as RIS
Report a correctionReport a correction
Record identifier22b4993d-6f62-474f-8fe9-1c465ef73b58
Record created2010-12-03
Record modified2016-05-09
Bookmark and share
  • Share this page with Facebook (Opens in a new window)
  • Share this page with Twitter (Opens in a new window)
  • Share this page with Google+ (Opens in a new window)
  • Share this page with Delicious (Opens in a new window)