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Creating a Translational Medicine Ontology Nature Precedings
Christine Denney; Colin Batchelor; Olivier Bodenreider; Sam Cheng; John Hart; John Hill; John Madden; Mark Musen; Elgar Pichler; Matthias Samwald; Sándor Szalma; Lynn Schriml; David Sedlock; Larisa Soldatova; Koji Sonoda; David Statham; Holger Stenzhorn; Patricia L. Whetzel; Elizabeth Wu; Susie Stephens.
*Abstract*
We, participants in the Translational Medicine Ontology activity of the World Wide Web Consortium’s Health Care and Life Sciences Interest Group ("http://esw.w3.org/topic/HCLSIG":http://esw.w3.org/topic/HCLSIG) and members of the National Center for Biomedical Ontology ("http://bioontology.org/":http://bioontology.org/), are developing a high-level, patient-centric ontology for translational medicine which will draw on existing domain ontologies and allow the integration of data throughout the drug development process.

*Introduction*
The pharmaceutical industry has historically focused on the development of novel blockbuster drugs....
Tipo: Poster Palavras-chave: Developmental Biology; Genetics & Genomics; Immunology; Molecular Cell Biology; Neuroscience; Pharmacology; Bioinformatics.
Ano: 2009 URL: http://precedings.nature.com/documents/3686/version/1
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The RNA Ontology (RNAO): An ontology for integrating RNA sequence and structure data Nature Precedings
Colin Batchelor; Thomas Bittner; Karen Eilbeck; Chris Mungall; Jane Richardson; Rob Knight; Jesse Stombaugh; Craig Zirbel; Eric Westhof; Neocles Leontis.
Biomedical Ontologies are intended to integrate diverse biomedical data to enable intelligent data-mining and facilitate translation of basic research into useful clinical knowledge. We present the first version of RNAO, an ontology for integrating RNA 3D structural, biochemical and sequence data. While each 3D data file depicts the structure of a specific molecule, such data have broader significance as representatives of classes of homologous molecules, which, while differing in sequence, generally share core structural features of functional importance. Thus, 3D structure data gain value by being linked to homologous sequences in genomic data and databases of sequence alignments. Likewise genomic data can increase in value by annotation of shared...
Tipo: Manuscript Palavras-chave: Chemistry; Genetics & Genomics; Bioinformatics.
Ano: 2009 URL: http://precedings.nature.com/documents/3561/version/1
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