ポスター発表
- 第1日 5月15日（火） ポスター会場
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1P-13 PDF
拡張重み更新型自己組織化マップを用いた食品機能性評価
In our previous study, we have developed a food functionality evaluation system that allows for simultaneous estimation of the multiple food functionalities from expression data of intracellular marker proteins using artificial neural network (ANN). This study attempted to simultaneously estimate the effect and action mechanism of food factor using extended-weight-updating self-organizing map (SOM) instead of ANN. To estimate human T-cell lymphotropic virus type 1-infected cell growth suppression activity, SOM was constructed using expression data of marker proteins as the feature vector, and activity value as the target vector. The SOM model could estimate the growth suppression activity of food factor with reasonable accuracy. Moreover, based on bibliographic information, food factor possessing the activity were clustered around compounds with a similar mechanism of action. These results suggest that the effect and action mechanism of food factor can be estimated simultaneously from the expression data of marker proteins using SOM.