In humans, oxidative stress is involved in the development of diabetes, cancer, hypertension, Alzheimers' disease, and heart failure. One of the mechanisms in the cellular defence against oxidative stress is the activation of the Nrf2-antioxidant response element (ARE) signalling pathway. Computation of activity, efficacy, and potency score of ARE signalling pathway and to propose a multi-level prediction scheme for the same is the main aim of the study as it contributes in a big amount to the improvement of oxidative stress in humans. Applying the process of knowledge discovery from data, required knowledge is gathered and then machine learning techniques are applied to propose a multi-level scheme. The validation of the proposed scheme is done using the K-fold cross-validation method and an accuracy of 90% is achieved for prediction of activity score for ARE molecules which determine their power to refine oxidative stress.

中文翻译：

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氧化应激信号通路的药物分子分类。

在人类中，氧化应激与糖尿病、癌症、高血压、阿尔茨海默病和心力衰竭的发展有关。细胞防御氧化应激的机制之一是激活 Nrf2-抗氧化反应元件 (ARE) 信号通路。计算 ARE 信号通路的活性、功效和效力评分并为此提出多层次预测方案是该研究的主要目的，因为它在很大程度上有助于改善人类的氧化应激。应用从数据中发现知识的过程，收集所需的知识，然后应用机器学习技术提出多层次的方案。