不均�?分布データ対応のヒストグラムタイプのメンバシップ関数自動生成機能を用いた遺伝子発現情報の解析

Chem-Bio Informatics Journal

臺場 昭人²  養王�? 正文²  伊藤 哲³  竹内 勤¹ 

[1] 慶應義塾大学�?医学部;東京農工大学工学府;富士レビオ株式会社

关键词: Microarray;    マイクロアレイ;    Gene Expression;    遺伝子発現;    Prediction of therapeutic efficacy;    治療効果予測;    Rheumatoid arthritis;    関節リウマチ;    Fuzzy Logic;    ファジー推論;   

DOI  :  10.1273/cbij.10.13

学科分类：生物化学/生物物理

来源: Chem-Bio Informatics Society

【 摘 要 】

References(20)The non-uniformity of gene expression data is one of the factors that make gene expression analysis difficult. Gene expression data often do not follow a normal distribution but rather various distributions within each group. Thus, it is impossible to apply basic statistical techniques such as the t-test. In this study, we have developed an analysis method for gene expression data obtained by microarrays using a fuzzy logic algorithm with original membership functions. The method automatically evaluates the data from a histogram of gene expression information for a patient group. Using this method, we predicted the efficacy of an anti-TNF-α treatment for rheumatoid arthritis. We created a prediction model for the effects of 14 weeks of anti-TNF-αtreatment based on the gene expression data from the peripheral blood of rheumatoid arthritis patients before the treatment. The model had a predictive success of 89% in the model-establishing data group, 94% in the training group, and 89% in the validation group. The results suggest that the method presented here could be an extremely effective tool for gene expression analysis.

【 授权许可】

Unknown