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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)
The objective of this thesis is to develop efficient text classification models to classify text documents. In usual text mining algorithms, a document is represented as a vector whose dimension is the number of distinct keywords in it, which can be very large. Consequently, traditional text classification can be computationally expensive. In this work,(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)
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)
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)
Overview Overview • • Overview of the Semantic Web Overview of the Semantic Web • • Semantic Web technologies Semantic Web technologies • • Semantic Web applications in biomedicine Semantic Web applications in biomedicine • • W3C Semantic Web W3C Semantic Web Health Care and Life Health Care and Life Sciences Interest Group Sciences Interest Group • •(More)
Ensuring drug safety is of paramount importance to the life sciences industry. It's critical that drugs are able not only to achieve the desired result but also to do so without harmful side effects. By identifying problems as early as possible in the drug discovery and development process, life sciences companies can avoid drug safety sagas, such as a(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)