Track 1: Research and resource discovery, collaboration and sharing
Track Chair: Bill Barnett, University of Indiana
The days of the sole investigator are receding quickly as modern science demands access to broad-based teams that apply complimentary knowledge and tools in new and creative ways. But forming a team with access to the right resources, collaborating over large distances and sharing/re-using results by other teams remain daunting challenges. This track will focus on newly emerging semantic-web based search and discovery tools that leverage advances in social networking and distance team collaboration sciences, and new models for data and tool sharing that can help reduce barriers to the next-generation of team-based science.
Track 2: Bedside to base pairs – From clinical observations to genetic discovery
Track Chair: Chunhua Weng, Columbia University
Electronic medical records have long held the promise of capturing detailed clinical observations that could be mined for genetic associations. New techniques are required for capturing, storing and analyzing observational EMR data to support complex phenotype detection. This track will focus on advances in data and text mining, data interaction and visualization methods, and data integration tools that unlock the deep potential for phenotype discovery for genetic association studies.
Track 3: Clinical care and clinical research work flow integration
Track Chair: Bernie La Salle, University of Utah
To date, clinical care and clinical research have existed as parallel, side-by-side processes. Much work has been done on exploiting EMR capabilities for study subject identification and recruitment. A significant amount of technical standards work has defined methods for integrating clinical care data collection with research data collection. This track will focus on the technical and regulatory barriers that exist in integrating clinical care and clinical research work flows, focusing on data collection, reporting, and adverse event detection.
Track 4: Emerging informatics platforms for integrated translational research
Track Chair: Tara Borlawsky, The Ohio State University
Clinical research informatics sits at the nexus of translational bioinformatics, clinical informatics and public health informatics. At its core reside challenges in integrating complex and heterogeneous data, including biological, clinical and population oriented data that span orders of magnitude in terms of the scale of the presented processes and the size of the involved data sets. Innovation models and technologies are emerging that attempt to harmonize across biological and clinical observations. This track will focus on emerging integrated informatics platforms that are being developed specifically to incorporate a wide range of highly disparate data into a uniform model, which utilizes ontologies for shared semantics to enable data sharing and analyses across previously siloed translational disciplines.