【論】Huang,2006,Incorporating biological knowledge ～

Desheng Huang and Wei Pan
Incorporating biological knowledge into distance-based clustering analysis of microarray gene expression data
Bioinformatics 2006 22(10):1259-1268
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・DNAマイクロアレイによる遺伝子機能推定の方法として、従来の統計的手法に生物学的知識（データベース）を取り入れた方法を提案する。
・データ
1.人工データ、3種
2.酵母（Saccharomyces cerevisiae）, 300サンプル [Hughes]
・実験
1.Two-class experiment
2.Three-class experiment
3.Model selection : Average silhouette と Five-fold CV の比較。

・方法「A two-step procedure is used. First, the shrinkage distance metric is used in any distance-based clustering method, e.g. K-medoids or hierarchical clustering, to cluster the genes with known functions. Second, while keeping the clustering results from the first step for the genes with known functions, the expression-based distance metric is used to cluster the remaining genes of unknown function, assigning each of them to either one of the clusters obtained in the first step or some new clusters.」
・概要「This article concerns incorporating biological knowledge into clustering genes for gene function discovery using microarray expression data, though the methodology can have more broad applications.」
・現状「In general, with relatively high noise levels of genomic data, it is recognized that incorporating biological knowledge into statistical analysis is a reliable way to maximize statistical efficiency and enhance the interpretability of analysis results.」

・生物学知識の取り入れ方、グラフの見方がわからず。