摘要 Data fusion has been widely applied to analyse di

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• 類型：已發表論文
• 日期：2015-11-04

摘要

Data fusion has been widely applied to analyse different sources of 資訊, combining all of them in a single multivariate model. This methodology is mandatory when different omic data sets must be integrated to fully understand an organism using a systems biology approach. Here, a data fusion procedure is presented to combine genomic, proteomic and phenotypic data sets gathered for Tobacco etch 病毒 (TEV). The genomic data correspond to random 突變s inserted in most viral genes. The proteomic data represent both the effect of these 突變s on the encoded 蛋白質s and the perturbation induced by the mutated 蛋白質s to their neighbours in the 蛋白質-蛋白質 interaction 網絡 (PPIN). Finally, the phenotypic trait evaluated for each mutant 病毒 is replicative fitness. To analyse these three sources of 資訊 a Partial Least Sq

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