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Integrative Data Mining in Functional Genomics of Brassica napus and Arabidopsis thaliana

机译:甘蓝型油菜和拟南芥功能基因组学中的集成数据挖掘

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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.
机译:通过多年的功能基因组研究,全球积累了各种形​​式的大量数据。发现和传播隐藏在这些数据中的知识是一个挑战。已经开发了许多计算方法来解决该问题。以对微阵列数据的分析为例,我们在过去十年中开发了许多数据挖掘策略和软件工具。看起来仍然不足以涵盖所有数据源。在本文中,我们以甘蓝型油菜和拟南芥这两种植物为例,总结了我们在芯片数据挖掘中的经验。我们介绍了一些成功的故事以及一些经验教训。我们要解决的领域问题是种子发育中的转录调控以及对病原体感染的防御反应。

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