A framework for annotating human genome in disease context

Identification of gene-disease association is crucial to understanding disease mechanism. A rapid increase in biomedical literatures, led by advances of genome-scale technologies, poses challenge for manually-curated-based annotation databases to characterize gene-disease associations effectively an...

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Bibliographic Details
Published inPloS one Vol. 7; no. 12; p. e49686
Main Authors Xu, Wei, Wang, Huisong, Cheng, Wenqing, Fu, Dong, Xia, Tian, Kibbe, Warren A, Lin, Simon M
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 10.12.2012
Public Library of Science (PLoS)
Subjects
Annotations
Anopheles
Bioinformatics
Biology
Cancer
Computational Biology - methods
Controlled vocabularies
Databases, Genetic
Disease
Downloading
Engineering
Genes
Genetic Predisposition to Disease
Genome, Human
Genomes
Genomics
Humans
Informatics
Knowledge base
Medicine
Natural language processing
Ontology
Semantics
Social and Behavioral Sciences
Software
Vocabulary, Controlled
Chicago Illinois
United States > US
Illinois
China
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Summary:Identification of gene-disease association is crucial to understanding disease mechanism. A rapid increase in biomedical literatures, led by advances of genome-scale technologies, poses challenge for manually-curated-based annotation databases to characterize gene-disease associations effectively and timely. We propose an automatic method-The Disease Ontology Annotation Framework (DOAF) to provide a comprehensive annotation of the human genome using the computable Disease Ontology (DO), the NCBO Annotator service and NCBI Gene Reference Into Function (GeneRIF). DOAF can keep the resulting knowledgebase current by periodically executing automatic pipeline to re-annotate the human genome using the latest DO and GeneRIF releases at any frequency such as daily or monthly. Further, DOAF provides a computable and programmable environment which enables large-scale and integrative analysis by working with external analytic software or online service platforms. A user-friendly web interface (doa.nubic.northwestern.edu) is implemented to allow users to efficiently query, download, and view disease annotations and the underlying evidences.
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Competing Interests: The authors have declared that no competing interests exist.
Conceived and designed the experiments: TX SML WAK. Performed the experiments: HSW WX DF WC. Contributed reagents/materials/analysis tools: HSW. Wrote the paper: TX SML WAK.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0049686