Semantic similarity in biomedical ontologies.
Semantic similarity in biomedical ontologies.
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DOI：
10.1371/journal.pcbi.1000443
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发表时间：
2009-07
影响因子：
4.3
通讯作者：
Couto FM
中科院分区：
文献类型：
--
作者：
Pesquita C;Faria D;Falcão AO;Lord P;Couto FM
近年来，本体论已成为生物医学研究的一个主流课题。当使用诸如本体论的公共模式描述生物实体时，可以借助于它们的注释来比较它们。这种类型的比较被称为语义相似性，因为它通过两个实体注释的相似性来评估它们之间的相关程度。语义相似性的生物医学本体的应用是最近的，然而，在过去的几年中已经发表了几项研究，描述和评估不同的方法。语义相似性已成为验证生物医学研究结果的重要工具，如基因聚类、基因表达数据分析、分子相互作用的预测和验证以及疾病基因优先级排序。我们回顾语义相似性的措施，应用于生物医学本体，并提出他们的分类，根据他们采用的策略：基于节点与基于边缘和成对与成组。我们还提出了比较评估研究，并讨论其结果的影响。我们调查现有的实现语义相似性的措施，我们描述的应用程序的例子，生物医学研究。这将阐明生物医学研究人员如何从语义相似性度量中受益，并帮助他们选择最适合他们研究的方法。生物医学本体正在朝着覆盖率、形式和集成的方向发展，它们用于注释越来越成为生物医学专家和应用自动注释程序创建比目前更高质量和完整性的语料库的焦点。鉴于语义相似性度量直接依赖于这些演变，我们可以期待看到它们获得更多的相关性，甚至成为今天生物医学研究中的序列相似性。
In recent years, ontologies have become a mainstream topic in biomedical research. When biological entities are described using a common schema, such as an ontology, they can be compared by means of their annotations. This type of comparison is called semantic similarity, since it assesses the degree of relatedness between two entities by the similarity in meaning of their annotations. The application of semantic similarity to biomedical ontologies is recent; nevertheless, several studies have been published in the last few years describing and evaluating diverse approaches. Semantic similarity has become a valuable tool for validating the results drawn from biomedical studies such as gene clustering, gene expression data analysis, prediction and validation of molecular interactions, and disease gene prioritization. We review semantic similarity measures applied to biomedical ontologies and propose their classification according to the strategies they employ: node-based versus edge-based and pairwise versus groupwise. We also present comparative assessment studies and discuss the implications of their results. We survey the existing implementations of semantic similarity measures, and we describe examples of applications to biomedical research. This will clarify how biomedical researchers can benefit from semantic similarity measures and help them choose the approach most suitable for their studies. Biomedical ontologies are evolving toward increased coverage, formality, and integration, and their use for annotation is increasingly becoming a focus of both effort by biomedical experts and application of automated annotation procedures to create corpora of higher quality and completeness than are currently available. Given that semantic similarity measures are directly dependent on these evolutions, we can expect to see them gaining more relevance and even becoming as essential as sequence similarity is today in biomedical research.
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影响因子：
3
作者：
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通讯作者：
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影响因子：
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作者：
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DOI：
10.1186/1747-5333-1-19
发表时间：
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期刊：
Journal of biomedical discovery and collaboration
影响因子：
--
作者：
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影响因子：
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作者：
Huang, Da Wei;Sherman, Brad T;Tan, Qina;Collins, Jack R;Alvord, W Gregory;Roayaei, Jean;Stephens, Robert;Baseler, Michael W;Lane, H Clifford;Lempicki, Richard A
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影响因子：
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作者：
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通讯作者：
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