首页> 外文会议>Second Critical Assessment of Microarray Data Analysis (CAMDA'01) Oct, 2001 null >USING FUNCTIONAL GENOMIC UNITS TO CORROBORATE USER EXPERIMENTS WITH THE ROSETTA COMPENDIUM
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USING FUNCTIONAL GENOMIC UNITS TO CORROBORATE USER EXPERIMENTS WITH THE ROSETTA COMPENDIUM

机译:使用功能基因组单位与《 Rosetta汇编》对用户实验进行校正

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The Rosetta data set opens the possibility of comparing an experimental microarray data set with a reference profile from the compendium. However, explaining this comparison in terms of individual genes could be a daunting task because of the sheer number of genes. Thus, we postulate a new strategy of modeling microarray data in terms of functional genomic units (FGUs). A functional genomic unit is a group of genes that carries out a certain biological function. We explored the possibility of defining the functional genomic units from the Gene Ontology (GO) annotation of the yeast genome. To visualize the tree structure of the GO, we have written a yeast genomic knowledge browser in Java, and integrated it with the microarray data. The pitfall of using the GO is that only a portion of the genes in the genome are functionally known or inferred. Thus, we further investigated an unsupervized learning method to identify those functional genomic units in the yeast genome. We have applied an established analysis method from digital signal processing, Independent Component Analysis (ICA), to the Rosetta data set. To further validate the utility of the Rosetta compendium, we have designed an experiment to investigate the yeast cells transfected with human Racl, a small GTPase protein of the Rho family, and demonstrated that functional genomic units helped us to corroborate our own microarray experiment with the Rosetta data set.
机译:Rosetta数据集提供了将实验性微阵列数据集与汇编中的参考资料进行比较的可能性。但是,由于基因数量庞大,因此用单个基因来解释这种比较可能是艰巨的任务。因此,我们提出了一种根据功能基因组单位(FGU)建模微阵列数据的新策略。功能基因组单位是一组执行特定生物学功能的基因。我们探索了从酵母基因组的基因本体论(GO)注释中定义功能基因组单位的可能性。为了可视化GO的树结构,我们用Java编写了一个酵母基因组知识浏览器,并将其与微阵列数据集成在一起。使用GO的陷阱在于,基因组中只有一部分基因在功能上是已知的或可推断的。因此,我们进一步研究了一种无超前的学习方法来鉴定酵母基因组中的那些功能基因组单元。我们已经将已建立的分析方法从数字信号处理独立分量分析(ICA)应用于Rosetta数据集。为了进一步验证Rosetta纲要的效用,我们设计了一个实验来研究用人Racl(Rho家族的一种小GTPase蛋白)转染的酵母细胞,并证明功能基因组可以帮助我们证实我们自己的微阵列实验。 Rosetta数据集。

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