Integrative data mining in functional genomics of brassica napus and arabidopsis thaliana

Authors:
Youlian Pan;Alain Tchagang;Hugo Bérubé;Sieu Phan;Heather Shearer;Ziying Liu;Pierre Fobert;Fazel Famili
Affiliations:
Institute for Information Technology, NRC, Ottawa, Ontario, Canada;Institute for Information Technology, NRC, Ottawa, Ontario, Canada;Institute for Information Technology, NRC, Ottawa, Ontario, Canada;Institute for Information Technology, NRC, Ottawa, Ontario, Canada;Plant Biotechnology Institute, NRC, Saskatoon, SK;Institute for Information Technology, NRC, Ottawa, Ontario, Canada;Plant Biotechnology Institute, NRC, Saskatoon, SK;Institute for Information Technology, NRC, Ottawa, Ontario, Canada
Venue:
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Year:
2010

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Abstract

Vast amount of data in various forms have been accumulated through many years of functional genomic research throughout the world. It is a challenge to discover and disseminate knowledge hidden in these data. Many computational methods have been developed to solve this problem. Taking analysis of the microarray data as an example, we spent the past decade developing many data mining strategies and software tools. It appears still insufficient to cover all sources of data. In this paper, we summarize our experiences in mining microarray data by using two plant species, Brassica napus and Arabidopsis thaliana, as examples. We present several successful stories and also a few lessons learnt. The domain problems that we dealt with were the transcriptional regulation in seed development and during defense response against pathogen infection.