ABSTRACT
Current healthcare is evolving to emphasize cost-effective care by leveraging results and outcomes of genomic and other advanced research efforts in clinical care and preventive health planning. Through a collaborative effort between the University of Tennessee Health Science Center (UTHSC) and Le Bonheur Children's Hospital (LBCH), the Biorepository and Integrative Genomics (BIG) Initiative was established to set up a pediatric-based DNA biorepository that can serve as a foundation for successful development of delivery platforms for predictive, preventive, and personalized medical services in Memphis, Tennessee, a historically disadvantaged community in the USA. In this paper, we describe the steps that were followed to establish the biorepository. We focused on domains that are essential for implementation of a biorepository for genomic research as an initial goal and identified patient consent, DNA extraction, storage and dissemination, and governance as essential components. Specific needs in each of these domains were addressed by respective solutions developed by multidisciplinary teams under the guidance of a governance model that involved experts from multiple hospital arenas and community members. The end result was the successful launch of a large-scale DNA biorepository, with patient consent greater than 75% in the first year. Our experience highlights the importance of performing pre-design research, needs assessment, and designing an ethically vetted plan that is cost-effective, easy to implement, and inclusive of the community that is served. We believe this biorepository model, with appropriate tailoring according to organizational needs and available resources, can be adopted and successfully applied by other small- to mid-sized healthcare organizations.
ABSTRACT
We present an article viewer application that allows a scientific reader to easily discover and share knowledge by linking genomics-related concepts to knowledge of disparate biomedical databases. High-throughput data streams generated by technical advancements have contributed to scientific knowledge discovery at an unprecedented rate. Biomedical Informaticists have created a diverse set of databases to store and retrieve the discovered knowledge. The diversity and abundance of such resources present biomedical researchers a challenge with knowledge discovery. These challenges highlight a need for a better informatics solution. We use a text mining algorithm, Genomine, to identify gene symbols from the text of a journal article. The identified symbols are supplemented with information from the GenoDB knowledgebase. Self-updating GenoDB contains information from NCBI Gene, Clinvar, Medgen, dbSNP, KEGG, PharmGKB, Uniprot, and Hugo Gene databases. The journal viewer is a web application accessible via a web browser. The features described herein are accessible on www.genotation.org The Genomine algorithm identifies gene symbols with an accuracy shown by .65 F-Score. GenoDB currently contains information regarding 59,905 gene symbols, 5633 drug-gene relationships, 5981 gene-disease relationships, and 713 pathways. This application provides scientific readers with actionable knowledge related to concepts of a manuscript. The reader will be able to save and share supplements to be visualized in a graphical manner. This provides convenient access to details of complex biological phenomena, enabling biomedical researchers to generate novel hypothesis to further our knowledge in human health. This manuscript presents a novel application that integrates genomic, proteomic, and pharmacogenomic information to supplement content of a biomedical manuscript and enable readers to automatically discover actionable knowledge.
