Lymphoma Prognostication from Expression Profiling Using a Combination Method of Boosting and Projective Adaptive Resonance Theory
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概要
- 論文の詳細を見る
In the present study, we developed the PART-robustBFCS method modified from PART-BFCS. This modeling was performed by using a bagging algorithm. In this algorithm, boosting result was assessed by using the data except one for model construction in order to repress the overfitting by modeling. We applied this method to the analysis of microarray data for the subclass identification of diffuse large B-cell lymphoma (DLBCL) patients. The results of our methods were superior to those of various other methods. The prediction accuracies were 75% for PART-BFCS and 79% for PART-robustBFCS.
- 社団法人 化学工学会の論文
- 2006-07-01
著者
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Honda Hiroyuki
Department of Biotechnology, School of Engineering, Nagoya University
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TAKAHASHI Hiro
Department of Biological Chemistry, College of Bioscience and Biotechnology, Chubu University
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高橋 広夫
中部大・応生・応生化
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Honda Hiroyuki
Department Of Bioengineering Tokyo Institute Of Technology
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Honda Hiroyuki
Department Of Biotechnology School Of Engineering Nagoya University
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Takahashi Hiro
Department Of Biotechnology School Of Engineering Nagoya University
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Takahashi Hiro
Department Of Biological Chemistry College Of Bioscience And Biotechnology Chubu University
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Takahashi Hiro
Department Of Biotechnology School Of Engineering Nagoya University:(present Office)college Of Biosc
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Takahashi Hiro
Research Fellow Of The Japan Society For The Promotion Of Science (jsps):department Of Biotechnology
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高橋 広夫
中部大学応用生物学部植物バイオ研究センター
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高橋 広夫
Department Of Biological Chemistry College Of Bioscience And Biotechnology Chubu University
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Honda Hiroyuki
Department Of Anesthesia Niigata City General Hospital
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Takahashi Hiro
Department Of Advanced Bioscience Faculty Of Agriculture Kinki University
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高橋 広夫
千葉大院・園芸
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