Variables Screening Method Based on the Algorithm of Combining Fruit Fly Optimization Algorithm and RBF Neural Network

Xu, Fei; Tao, Youtian

doi:10.2991/iccia.2012.377

Cited by 2 publications

(1 citation statement)

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“…The method of MIV, proposed by Dombi, is the index of much consequence to illustrate how to use the neural network to select the independent variables that have a great impact on the dependent variables. It has been considered one of the best indexes to assess the assigned coefficient values up to now . The plus or minus sign represents the positive or negative correlation; the absolute value represents the influence degree.…”

Section: Methodsmentioning

confidence: 99%

A Novel Approach to Active Compounds Identification Based on Support Vector Regression Model and Mean Impact Value

Jiang

Zhang

et al. 2013

Chem Biol Drug Des

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Traditionally, active compounds were discovered from natural product extracts by bioassay-guided fractionation, which was with high cost and low efficiency. A well-trained support vector regression model based on mean impact value was used to identify lead active compounds on inhibiting the proliferation of the HeLa cells in curcuminoids from Curcuma longa L. Eight constituents possessing the high absolute mean impact value were identified to have significant cytotoxicity, and the cytotoxic effect of these constituents was partly confirmed by subsequent MTT (3-(4, 5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assays and previous reports. In the dosage range of 0.2-211.2, 0.1-140.2, 0.2-149.9 μm, 50% inhibiting concentrations (IC50 ) of curcumin, demethoxycurcumin, and bisdemethoxycurcumin were 26.99 ± 1.11, 19.90 ± 1.22, and 35.51 ± 7.29 μm, respectively. It was demonstrated that our method could successfully identify lead active compounds in curcuminoids from Curcuma longa L. prior to bioassay-guided separation. The use of a support vector regression model combined with mean impact value analysis could provide an efficient and economical approach for drug discovery from natural products.

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Section: Methodsmentioning

confidence: 99%