Fuzzy Adaptive Least Squares and Its Use in Quantitative Structure-Activity Relationships
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概要
- 論文の詳細を見る
Fuzzy adaptive least squares (FALS), a pattern recognition method designed to correlate molecular structure with activity rating, has been developed. A novel feature of FALS is that the degree to which each sample belongs to an activity class is given using a membership function. The algorithm involves an iterative modification of forcing factors to maximize the sum of the membership function values over all samples. This paper first describes the method and calculation procedure of FALS89 (1989 version of FALS), and then shows its application to the correlation of structure with a potency rating of anticarcinogenic mitomycin derivatives and arginine-vasopressin antagonists. FALS89 applied to these samples showed considerably high reliability in both recognition and leave-one-out prediction.
- 公益社団法人日本薬学会の論文
- 1990-12-25
著者
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広野 修一
北里大学薬学部
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広野 修一
Department Of Pharmaceutical Sciences Kitasato University
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森口 郁生
School Of Pharmaceutical Sciences Kitasato University
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松下 泰雄
School of Pharmaceutical Sciences, Kitasato University
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劉 謙
School Of Pharmaceutical Sciences Kitasato University
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広野 修一
School of Pharmaceutical Sciences, Kitasato University
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森口 郁生
北里大
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中川 祟子
School of Pharmaceutical Sciences, Kitasato University
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松下 泰雄
School Of Pharmaceutical Sciences Kitasato University
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中川 祟子
School Of Pharmaceutical Sciences Kitasato University
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Moriguchi I
School Of Pharmaceutical Sciences Kitasato University
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