Bidaut Ghislain
University of Pennsylvania School of Medicine, Philadelphia, USA.
Methods Mol Biol. 2007;408:1-18. doi: 10.1007/978-1-59745-547-3_1.
Expression data from knockout mutants is a powerful tool for gene function inference, permitting observation of the phenotype of a deleted gene on the organismal scale. A computational method is demonstrated herein to assess gene function from gene expression measured in deletion mutants using Bayesian decomposition, a matrix factorization technique that permits the extraction of patterns and functional units from the data, i.e., sets of genes belonging to the same pathways shared by sets of knockout mutants. ClutrFree, a cluster visualization program is used to aid in the interpretation of functional units and the assessment of gene functions for a subset of unknown genes.
基因敲除突变体的表达数据是推断基因功能的有力工具，可在生物体水平上观察缺失基因的表型。本文展示了一种计算方法，该方法使用贝叶斯分解从缺失突变体中测量的基因表达来评估基因功能，贝叶斯分解是一种矩阵分解技术，可从数据中提取模式和功能单元，即属于基因敲除突变体集合所共有的相同通路的基因集。使用聚类可视化程序ClutrFree来辅助解释功能单元，并评估一部分未知基因的基因功能。
