环境条件、治疗和暴露本体论(ECTO):将毒理学和暴露与人类健康及其他联系起来。

IF 1.6 3区 工程技术 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Lauren E Chan, Anne E Thessen, William D Duncan, Nicolas Matentzoglu, Charles Schmitt, Cynthia J Grondin, Nicole Vasilevsky, Julie A McMurry, Peter N Robinson, Christopher J Mungall, Melissa A Haendel
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引用次数: 0

摘要

背景:评估环境暴露对生物体健康的影响是现代生物医学的一个关键目标,在环境污染和化学品日益严重的时代,这一点至关重要。环境健康利用了许多不同的研究方法,并生成了各种类型的数据。然而,迄今为止,还没有一个全面的数据库能代表环境健康数据的全部内容。由于数据库之间缺乏互操作性,因此需要整合这些资源的工具。在本手稿中,我们介绍了环境条件、处理和暴露本体论(ECTO),这是一个与物种无关的本体论,重点关注因饮食、工作或研究活动等自然和实验过程而发生的暴露事件。ECTO 旨在用于协调环境健康数据资源,以支持跨研究整合和机制发现推论:ECTO 是一种本体论,用于描述生物体暴露,如毒理学研究、环境变量、饮食特征和来自调查的患者报告数据。ECTO 利用暴露本体(ExO)中建立的基础模型。ECTO 是通过手工整理和 Dead Simple OWL Design Patterns(DOSDP)相结合的方式开发的,包含 2700 多个环境暴露术语,并融合了化学和环境本体。ECTO 是一个开放式生物和生物医学本体论(OBO)基金会本体论,旨在实现与其他本体论的互操作性、重复使用和公理化。ECTO术语已被用于蒙多疾病本体的公理中,以表示由环境因素引起或影响的疾病,以及用于个性化环境与基因研究(PEGS)的调查编码:我们构建的 ECTO 符合开放生物和生物医学本体论 (OBO) 基金会的原则,以增加环境健康与其他生物学领域之间的转化机会。ECTO 的贡献者群体在不断壮大,其中包括毒理学家、公共卫生流行病学家和医疗保健提供者,他们为之前被确定为空白的领域提供了必要的专业知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The Environmental Conditions, Treatments, and Exposures Ontology (ECTO): connecting toxicology and exposure to human health and beyond.

The Environmental Conditions, Treatments, and Exposures Ontology (ECTO): connecting toxicology and exposure to human health and beyond.

The Environmental Conditions, Treatments, and Exposures Ontology (ECTO): connecting toxicology and exposure to human health and beyond.

The Environmental Conditions, Treatments, and Exposures Ontology (ECTO): connecting toxicology and exposure to human health and beyond.

Background: Evaluating the impact of environmental exposures on organism health is a key goal of modern biomedicine and is critically important in an age of greater pollution and chemicals in our environment. Environmental health utilizes many different research methods and generates a variety of data types. However, to date, no comprehensive database represents the full spectrum of environmental health data. Due to a lack of interoperability between databases, tools for integrating these resources are needed. In this manuscript we present the Environmental Conditions, Treatments, and Exposures Ontology (ECTO), a species-agnostic ontology focused on exposure events that occur as a result of natural and experimental processes, such as diet, work, or research activities. ECTO is intended for use in harmonizing environmental health data resources to support cross-study integration and inference for mechanism discovery.

Methods and findings: ECTO is an ontology designed for describing organismal exposures such as toxicological research, environmental variables, dietary features, and patient-reported data from surveys. ECTO utilizes the base model established within the Exposure Ontology (ExO). ECTO is developed using a combination of manual curation and Dead Simple OWL Design Patterns (DOSDP), and contains over 2700 environmental exposure terms, and incorporates chemical and environmental ontologies. ECTO is an Open Biological and Biomedical Ontology (OBO) Foundry ontology that is designed for interoperability, reuse, and axiomatization with other ontologies. ECTO terms have been utilized in axioms within the Mondo Disease Ontology to represent diseases caused or influenced by environmental factors, as well as for survey encoding for the Personalized Environment and Genes Study (PEGS).

Conclusions: We constructed ECTO to meet Open Biological and Biomedical Ontology (OBO) Foundry principles to increase translation opportunities between environmental health and other areas of biology. ECTO has a growing community of contributors consisting of toxicologists, public health epidemiologists, and health care providers to provide the necessary expertise for areas that have been identified previously as gaps.

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来源期刊
Journal of Biomedical Semantics
Journal of Biomedical Semantics MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
4.20
自引率
5.30%
发文量
28
审稿时长
30 weeks
期刊介绍: Journal of Biomedical Semantics addresses issues of semantic enrichment and semantic processing in the biomedical domain. The scope of the journal covers two main areas: Infrastructure for biomedical semantics: focusing on semantic resources and repositories, meta-data management and resource description, knowledge representation and semantic frameworks, the Biomedical Semantic Web, and semantic interoperability. Semantic mining, annotation, and analysis: focusing on approaches and applications of semantic resources; and tools for investigation, reasoning, prediction, and discoveries in biomedicine.
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