| Co-Investigator(Kenkyū-buntansha) |
KURIKI Satoshi 統計数理研究所, 数理・推論研究系, 教授 (90195545)
FUJISAWA Hironori 統計数理研究所, 数理・推論研究系, 准教授 (00301177)
HENMI Masayuki 統計数理研究所, 数理・推論研究系, 准教授 (80465921)
MATSUURA Masaaki (公財)がん研究会, ゲノムセンター情報解析部門, 部門長 (40173794)
MANO Shuhei 統計数理研究所, 数理・推論研究系, 准教授 (20372948)
KOMORI Osamu 統計数理研究所, 統計思考院, 特任助教 (60586379)
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| Budget Amount *help |
¥42,250,000 (Direct Cost: ¥32,500,000、Indirect Cost: ¥9,750,000)
Fiscal Year 2012: ¥8,060,000 (Direct Cost: ¥6,200,000、Indirect Cost: ¥1,860,000)
Fiscal Year 2011: ¥8,970,000 (Direct Cost: ¥6,900,000、Indirect Cost: ¥2,070,000)
Fiscal Year 2010: ¥7,800,000 (Direct Cost: ¥6,000,000、Indirect Cost: ¥1,800,000)
Fiscal Year 2009: ¥7,150,000 (Direct Cost: ¥5,500,000、Indirect Cost: ¥1,650,000)
Fiscal Year 2008: ¥10,270,000 (Direct Cost: ¥7,900,000、Indirect Cost: ¥2,370,000)
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| Research Abstract |
Statistical methods to achieve scientific results conducted from genomics and omics data have been exploited. In particular, for prediction of phenotypes (disease type, treatment effect, prognosis) we enhanced to implement several proposals by a fusion between statistics and machine learning. The boosting method by maximization of Area Under Curve is applied to gene expression data. LASSO clustering is proposed to select genes for detecting subtypes in breast cancer patients.
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