Exploring the effects a chemical compound has on a species takes a considerable experimental effort. Appropriate methods for estimating and suggesting new effects can dramatically reduce the work needed to be done by a laboratory. In this paper we explore the suitability of using a knowledge graph embedding approach for ecotoxicological effect prediction. A knowledge graph has been constructed from publicly available data sets, including a species taxonomy and chemical classification and similarity. The publicly available effect data is integrated to the knowledge graph using ontology alignment techniques. Our experimental results show that the knowledge graph based approach improves the selected baselines.
翻译:探索化学化合物对物种的影响需要大量实验努力。估算和提出新影响的适当方法可以大大减少实验室需要开展的工作。在本文件中,我们探讨了使用知识图嵌入方法进行生态毒理效应预测是否合适。知识图是根据公开可得的数据集构建的,包括物种分类和化学分类及相似性。公开可得的效果数据是使用本体调整技术与知识图相结合的。我们的实验结果显示,知识图方法改善了选定的基线。