Philip Anderson, Andreas Thor, Joseph Benik, L. Raschid, Maria-Esther Vidal
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引用次数: 8
摘要
标注图数据集是科学知识的自然表示。它们在生命科学和健康科学中很常见,在这些科学中,基因、蛋白质或临床试验等概念用来自本体论的受控词汇术语进行注释。我们提出了一个工具,PAnG (Patterns in Annotation Graphs),它基于图摘要和密集子图的互补方法。图形摘要的元素对应于模式,其可视化可以提供对底层知识的解释。科学家可以使用人工智能来提出假设和进行探索。
Annotation graph datasets are a natural representation of scientific knowledge. They are common in the life sciences and health sciences, where concepts such as genes, proteins or clinical trials are annotated with controlled vocabulary terms from ontologies. We present a tool, PAnG (Patterns in Annotation Graphs), that is based on a complementary methodology of graph summarization and dense subgraphs. The elements of a graph summary correspond to a pattern and its visualization can provide an explanation of the underlying knowledge. Scientists can use PAnG to develop hypotheses and for exploration.