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BACKGROUND A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic(More)
There is an abundance of information about drugs available on the Web. Data sources range from medicinal chemistry results, over the impact of drugs on gene expression, to the outcomes of drugs in clinical trials. These data are typically not connected together, which reduces the ease with which insights can be gained. Linking Open Drug Data (LODD) is a(More)
Performing sequence homology searches against DNA or protein sequence databases is an essential bioinformatics task. Past research efforts have been primarily concerned with the development of sensitive and fast sequence homology search algorithms outside of the relational database management system (RDBMS). Oracle Data Mining (ODM) BLAST enables BLAST to(More)
BACKGROUND Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for(More)
The integration of disparate biomedical data continues to be a challenge for drug discovery efforts. Semantic Web technologies provide the capability to more easily aggregate data and thus can be utilized to improve the efficiency of drug discovery. We describe an implementation of a Semantic Web infrastructure that utilizes the scalable Oracle RDF Data(More)
BACKGROUND Translational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototype Translational Medicine Knowledge Base (TMKB) capable of answering questions relating to clinical practice and pharmaceutical drug discovery. RESULTS We(More)
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Members of the W3C Health Care and Life Sciences Interest Group (HCLS IG) have published a variety of genomic and drug-related datasets as Resource Description Framework (RDF) triples. This experience has helped the interest group define a general data workflow for mapping health care and life science (HCLS) data to RDF and linking it with other Linked Data(More)
As database management systems expand their array of analytical functionality, they become powerful research engines for biomedical data analysis and drug discovery. Databases can hold most of the data types commonly required in life sciences and consequently can be used as flexible platforms for the implementation of knowledgebases. Performing data(More)
Advances in the biological sciences are allowing pharmaceutical companies to meet the health care crisis with drugs that are more suitable for preventive and tailored treatment, thereby holding the promise of enabling more cost effective care with greater efficacy and reduced side effects. However, this shift in business model increases the need for(More)