Abstract:
:Ontologies are now pervasive in biomedicine, where they serve as a means to standardize terminology, to enable access to domain knowledge, to verify data consistency and to facilitate integrative analyses over heterogeneous biomedical data. For this purpose, research on biomedical ontologies applies theories and methods from diverse disciplines such as information management, knowledge representation, cognitive science, linguistics and philosophy. Depending on the desired applications in which ontologies are being applied, the evaluation of research in biomedical ontologies must follow different strategies. Here, we provide a classification of research problems in which ontologies are being applied, focusing on the use of ontologies in basic and translational research, and we demonstrate how research results in biomedical ontologies can be evaluated. The evaluation strategies depend on the desired application and measure the success of using an ontology for a particular biomedical problem. For many applications, the success can be quantified, thereby facilitating the objective evaluation and comparison of research in biomedical ontology. The objective, quantifiable comparison of research results based on scientific applications opens up the possibility for systematically improving the utility of ontologies in biomedical research.
journal_name
Brief Bioinformjournal_title
Briefings in bioinformaticsauthors
Hoehndorf R,Dumontier M,Gkoutos GVdoi
10.1093/bib/bbs053subject
Has Abstractpub_date
2013-11-01 00:00:00pages
696-712issue
6eissn
1467-5463issn
1477-4054pii
bbs053journal_volume
14pub_type
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journal_title:Briefings in bioinformatics
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
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abstract::Gene expression data have played an essential role in many biomedical studies. When the number of genes is large and sample size is limited, there is a 'lack of information' problem, leading to low-quality findings. To tackle this problem, both horizontal and vertical data integrations have been developed, where verti...
journal_title:Briefings in bioinformatics
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更新日期:2020-08-14 00:00:00
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更新日期:2006-06-01 00:00:00
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pub_type: 杂志文章
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更新日期:2020-12-01 00:00:00
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更新日期:2015-07-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
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更新日期:2020-06-10 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bbp008
更新日期:2009-07-01 00:00:00
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journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/3.1.18
更新日期:2002-03-01 00:00:00
abstract::High-throughput omics data are generated almost with no limit nowadays. It becomes increasingly important to integrate different omics data types to disentangle the molecular machinery of complex diseases with the hope for better disease prevention and treatment. Since the relationship among different omics data featu...
journal_title:Briefings in bioinformatics
pub_type: 杂志文章
doi:10.1093/bib/bby115
更新日期:2018-11-29 00:00:00
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journal_title:Briefings in bioinformatics
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更新日期:2020-06-26 00:00:00
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pub_type: 杂志文章
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更新日期:2021-01-18 00:00:00
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更新日期:2020-09-21 00:00:00
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pub_type: 杂志文章
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更新日期:2020-05-21 00:00:00
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更新日期:2020-05-21 00:00:00
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更新日期:2019-03-25 00:00:00
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更新日期:2020-12-18 00:00:00
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