Identifying Missing IS-A Relations in Orphanet Rare Disease Ontology

Identifying Missing IS-A Relations in Orphanet Rare Disease Ontology
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识别孤儿罕见疾病本体中缺失的 IS-A 关系

DOI:
10.1109/bibm55620.2022.9995614
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发表时间:
2022
期刊:
2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM
影响因子:
--
通讯作者:
Cui, Licong
Cui, Licong
中科院分区:
--
文献类型:
--
作者:
Mohtashamian, Maryamsadat;Abeysinghe, Rashmie;Hao, Xubing;Cui, Licong

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孤儿罕见病本体(ORDO)提供了一个结构化的词汇表封装罕见病。ORDO的下游应用依赖于它的准确性来有效地执行任务。在本文中,我们实现了一个自动化的质量保证管道来识别ORDO中缺失的is-a关系。我们首先从概念名称中获得词汇特征。然后生成相关和不相关的特征共享概念对,其中特征共享概念对可以进一步生成派生的术语对。如果不相关的特征共享概念对和相关的特征共享概念对产生相同的派生术语对,那么我们建议在不相关的特征共享概念对之间存在潜在的缺失is-a关系。将此方法应用于202206-27年发布的ORDO,我们获得了705个潜在的缺失is-a关系。利用统一医学语言系统中的外部本体信息,我们验证了164个缺失的is-a关系。这表明我们的方法是一种在ORDO中审计is-a关系的有前途的方法,尽管仍然需要进一步的领域专家评估来验证识别出的剩余的潜在缺失的is-a关系。
The Orphanet Rare Disease Ontology (ORDO) provides a structured vocabulary encapsulating rare diseases. Downstream applications of ORDO depend on its accuracy to effectively perform their tasks. In this paper, we implement an automated quality assurance pipeline to identify missing is-a relations in ORDO. We first obtain lexical features from concept names. Then we generate related and unrelated feature sharing concept-pairs, where a feature sharing concept-pair can further generate derived term-pairs. If an unrelated and related feature sharing concept-pair generate the same derived term-pair, then we suggest a potential missing is-a relation between the unrelated feature sharing concept-pair. Applying this approach on the 202206-27 release of ORDO, we obtained 705 potential missing is-a relations. Leveraging external ontological information in the Unified Medical Language System, we validated 164 missing is-a relations. This indicates that our approach is a promising way to audit is-a relations in ORDO, even though further domain expert evaluation is still needed to validate the remaining potential missing is-a relations identified.
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