Multi-class Mode of Action Classification of Toxic Compounds Using Logic Based Kernel Methods.
Multi-class Mode of Action Classification of Toxic Compounds Using Logic Based Kernel Methods.
复制标题
使用基于逻辑的内核方法对有毒化合物进行多类作用模式分类。
DOI：
10.1002/minf.201000083
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发表时间：
2010
影响因子：
3.6
通讯作者：
Lodhi H
中科院分区：
文献类型：
--
作者：
Lodhi H
毒性预测对于药物设计和有效治疗剂的开发是必不可少的。在本文中，我们提出了一个在硅片的战略，以确定有毒化合物的作用模式，这是基于使用一种新的逻辑为基础的内核方法。该技术使用支持向量机与内核构造从一阶规则诱导的归纳逻辑编程系统。它通过使用分治归约策略构建多类模型，该策略将多类分成二进制组，并递归地解决每个问题，从而生成底层决策列表结构。为了评估化学信息学问题，如预测毒理学的方法的有效性，我们将其应用于水生系统中的毒性分类。该方法被用来识别和分类442化合物的作用方式。实验结果表明，该技术成功地分类有毒化合物，可以用于评估环境风险。将所提出的多类方案的性能与标准的多类归纳逻辑编程算法和多类支持向量机进行实验比较，得出了统计上显着的结果，并证明了该方法在识别各种有毒化合物方面的潜在能力和益处机制。
Toxicity prediction is essential for drug design and development of effective therapeutics. In this paper we present an in silico strategy, to identify the mode of action of toxic compounds, that is based on the use of a novel logic based kernel method. The technique uses support vector machines in conjunction with the kernels constructed from first order rules induced by an Inductive Logic Programming system. It constructs multi‐class models by using a divide and conquer reduction strategy that splits multi‐classes into binary groups and solves each individual problem recursively hence generating an underlying decision list structure. In order to evaluate the effectiveness of the approach for chemoinformatics problems like predictive toxicology, we apply it to toxicity classification in aquatic systems. The method is used to identify and classify 442 compounds with respect to the mode of action. The experimental results show that the technique successfully classifies toxic compounds and can be useful in assessing environmental risks. Experimental comparison of the performance of the proposed multi‐class scheme with the standard multi‐class Inductive Logic Programming algorithm and multi‐class Support Vector Machine yields statistically significant results and demonstrates the potential power and benefits of the approach in identifying compounds of various toxic mechanisms.