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. © 2010 Springer-Verlag.
CITATION STYLE
Pan, Y., Tchagang, A., Bérubé, H., Phan, S., Shearer, H., Liu, Z., … Famili, F. (2010). Integrative data mining in functional genomics of Brassica napus and Arabidopsis thaliana. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6098 LNAI, pp. 92–101). https://doi.org/10.1007/978-3-642-13033-5_10
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