【論】Kadota,2003,Detection of genes with tissue～

Koji Kadota, Shin-ichiro Nishimura, Hidemasa Bono, Shugo Nakamura, Yoshihide Hayashizaki, Yasushi Okazaki, and Katsutoshi Takahashi
Detection of genes with tissue-specific expression patterns using Akaike's information criterion procedure
Physiol Genomics 12: 251-259, 2003.
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・赤池情報量基準（AIC）を遺伝子発現解析に応用。マウスのデータを使い、各体組織（筋肉、肺、脳など）に特異的に発現する遺伝子を抽出する。
・使用データ：mouse cDNA microarray data, 49 adult and embryonic mouse tissues and 14,610 clones, http://read.gsc.riken.go.jp/
・比較対象の抽出法：パターンマッチング法

・AICが最小のときの遺伝子を取り出すというハナシですが、イメージが湧かない・・・orz

・「First, in the two-color competitive hybridization assays on cDNA microarrrays customarily used in most of the published studies, there are often strongly biased origins of transcripts on the glass slides.」
・「Second, among the expression levels of particular tissues whose levels are significantly different from those of other tissues, similar intra-tissue levels cannot always be identified.」
・「Akaike's information criterion (AIC), introduced almost 30 years ago by H. Akaike, is an information criterion for the identification of an optimal model from a class of competing models.」
・「The (n+s) observations are normalized by subtractiong the mean and dividing by the standard deviation,」
・「The most significant advantage of the method is that it is possible to arrive at an objective decision because the method does not require the selection of a significance level such as 1% or 5%.」
・「The advantages of the method we proposed here are 1) the acquired answer is objective and 2) various situations (e.g., single outlier, multiple lowest or highest outliers, two-sided and grouped cases) can be treated equally.」