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          Institute: MPI für molekulare Genetik     Collection: Department of Computational Molecular Biology     Display Documents



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ID: 447350.0, MPI für molekulare Genetik / Department of Computational Molecular Biology
Clinical Diagnostics with Semantic Similarity Searches in Ontologies.
Authors:Köhler, Sebastian; Schulz, Marcel H.; Bauer, Sebastian; Dölken, Sandra; Ott, Claus E.; Mundlos, Christine; Horn, Denise; Mundlos, Stefan; Robinson, Peter N.
Language:English
Date of Publication (YYYY-MM-DD):2009-10-01
Title of Journal:The American Journal of Human Genetics
Journal Abbrev.:Am. J. Hum. Genet.
Volume:85
Issue / Number:4
Start Page:457
End Page:464
Copyright:2009 The American Society of Human Genetics. All rights reserved.
Review Status:not specified
Audience:Experts Only
Abstract / Description:The differential diagnostic process attempts to identify candidate diseases that best explain a set of clinical features. This process can be complicated by the fact that the features can have varying degrees of specificity, as well as by the presence of features unrelated to the disease itself. Depending on the experience of the physician and the availability of laboratory tests, clinical abnormalities may be described in greater or lesser detail. We have adapted semantic similarity metrics to measure phenotypic similarity between queries and hereditary diseases annotated with the use of the Human Phenotype Ontology (HPO) and have developed a statistical model to assign p values to the resulting similarity scores, which can be used to rank the candidate diseases. We show that our approach outperforms simpler term-matching approaches that do not take the semantic interrelationships between terms into account. The advantage of our approach was greater for queries containing phenotypic noise or imprecise clinical descriptions. The semantic network defined by the HPO can be used to refine the differential diagnosis by suggesting clinical features that, if present, best differentiate among the candidate diagnoses. Thus, semantic similarity searches in ontologies represent a useful way of harnessing the semantic structure of human phenotypic abnormalities to help with the differential diagnosis. We have implemented our methods in a freely available web application for the field of human Mendelian disorders.
Comment of the Author/Creator:Corresponding author.
Peter N. Robinson
External Publication Status:published
Document Type:Article
Communicated by:Martin Vingron
Affiliations:MPI für molekulare Genetik
External Affiliations:1.Institute for Medical Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany;
2.Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany;
3.International Max Planck Research School for Computational Biology and Scientific Computing, 14195 Berlin, Germany;
4.Allianz Chronischer Seltener Erkrankungen (ACHSE), 14050 Berlin, Germany.
Identifiers:URL:http://www.cell.com/AJHG/abstract/S0002-9297(09)00...
DOI:10.1016/j.ajhg.2009.09.003
ISSN:1537-6605
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