OBCS: The Ontology of Biological and Clinical Statistics
OBCS: The Ontology of Biological and Clinical Statistics
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OBCS：生物和临床统计学本体论
DOI：
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发表时间：
2014
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通讯作者：
Y. He
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文献类型：
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作者：
Jie Zheng;M. Harris;A. Masci;Yu Lin;A. Hero;Barry Smith;Y. He
统计学在生物学和临床研究中起着至关重要的作用。在大（临床）数据时代，这一角色变得更加突出，因为统计将成为未来虚拟临床试验和元试验的核心工具。为了促进统计实体的逻辑一致表示和分类，我们开发了生物和临床统计本体（OBCS）。OBCS扩展了生物医学研究本体（OBI）， OBI是开放生物/生物医学本体（OBO）铸造的一个本体，得到了大约20个社区的支持。OBCS从OBI导入所有与统计相关的术语。此外，OBCS还增加了许多其他与统计相关的术语，以填补统计表示方面的空白。OBCS的开发采用了自顶向下和自底向上相结合的方法。自顶向下方法的工作原理是从高层结构的角度调查统计工作流程，并在OBCS中缺少新术语时生成新术语。自下而上的方法是通过研究特定的生物学和临床统计分析用例，在现有的高级本体类下创建相应的术语。目前，OBCS包含686个术语，其中包括从OBI导入的381个类和OBCS特有的147个类。在本文中，我们将介绍OBCS发展的基本原理、历史和现状。此外，还提供了一个生物学和一个临床用例来说明OBCS的潜在应用。生物学用例涉及使用接种了三价灭活流感疫苗的人类受试者的血液样本进行的微阵列实验的统计数据分析的OBCS表示。临床用例使用从电子出院摘要中获得的数据分析护理服务的临床结果。OBCS将进一步发展。将根据社区需求和生物/临床用例纳入更多统计术语。OBCS项目和源代码可在http://obcs.googlecode.com上获得。关键词：本体，统计学，数据分析，生物学和临床研究ICBO 2014论文集
Statistics play a critical role in biological and clinical research. In the era of Big (clinical) Data, this role becomes even more prominent, since statistics will serve as the central tool in the virtual clinical trials and meta-trials of the future. To promote logically consistent representation and classification of statistical entities, we have developed the Ontology of Biological and Clinical Statistics (OBCS). OBCS extends the Ontology of Biomedical Investigations (OBI) that is an ontology of the Open Biological/Biomedical Ontologies (OBO) Foundry and is supported by some 20 communities. OBCS imports all statistics-related terms from OBI. In addition, many other statistics related terms were added to OBCS to fill up the gaps in statistics representation. A combination of top-down and bottom-up methods is used in the OBCS development. The top-down approach works by surveying statistics workflows from the perspective of high-level structuring and generating new terms in OBCS when they are missing. The bottom-up method is applied by studying specific biological and clinical statistical analysis use cases, creating corresponding terms under existing high-level ontology classes. Currently, OBCS contains 686 terms, including 381 classes imported from OBI and 147 classes specific to OBCS. In this paper, we will introduce the rationale, history, and current status of the OBCS development. Furthermore, one biological and one clinical use cases are provided to illustrate potential applications of OBCS. The biological use case involves an OBCS representation of a statistical data analysis of a microarray experiment conducted using blood samples from human subjects vaccinated with a trivalent inactivated influenza vaccine. The clinical use case analyzes clinical outcomes of nursing services using data obtained from electronic hospital discharge abstracts. The OBCS will be further developed. More statistics terms will be included based on community needs and biological/clinical use cases. The OBCS project and source code are available at http://obcs.googlecode.com. Keywords— ontology, statistics, data analysis, biological and clinical research ICBO 2014 Proceedings