Title |
Querying phenotype-genotype relationships on patient datasets using semantic web technology: the example of cerebrotendinous xanthomatosis
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Published in |
BMC Medical Informatics and Decision Making, July 2012
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DOI | 10.1186/1472-6947-12-78 |
Pubmed ID | |
Authors |
María Taboada, Diego Martínez, Belén Pilo, Adriano Jiménez-Escrig, Peter N Robinson, María J Sobrido |
Abstract |
Semantic Web technology can considerably catalyze translational genetics and genomics research in medicine, where the interchange of information between basic research and clinical levels becomes crucial. This exchange involves mapping abstract phenotype descriptions from research resources, such as knowledge databases and catalogs, to unstructured datasets produced through experimental methods and clinical practice. This is especially true for the construction of mutation databases. This paper presents a way of harmonizing abstract phenotype descriptions with patient data from clinical practice, and querying this dataset about relationships between phenotypes and genetic variants, at different levels of abstraction. |
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United Kingdom | 1 | 25% |
India | 1 | 25% |
Demographic breakdown
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Scientists | 2 | 50% |
Practitioners (doctors, other healthcare professionals) | 2 | 50% |
Mendeley readers
Geographical breakdown
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Brazil | 3 | 5% |
United Kingdom | 1 | 2% |
United States | 1 | 2% |
Spain | 1 | 2% |
Unknown | 54 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 14 | 23% |
Student > Ph. D. Student | 10 | 17% |
Student > Bachelor | 8 | 13% |
Student > Master | 7 | 12% |
Professor > Associate Professor | 5 | 8% |
Other | 13 | 22% |
Unknown | 3 | 5% |
Readers by discipline | Count | As % |
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Computer Science | 13 | 22% |
Agricultural and Biological Sciences | 8 | 13% |
Biochemistry, Genetics and Molecular Biology | 4 | 7% |
Engineering | 3 | 5% |
Other | 12 | 20% |
Unknown | 7 | 12% |