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Informatics

The Biomedical Informatics Component (BIC) of the University of Chicago ITM applies expertise in information technology and data management to enhance the conduct of clinical and translational research. The BIC: (i) provides services and support in information technology and data management tailored to the programs in clinical and translational science at UC, (ii) provides informatics education and training to scientists and physicians which enables them to best deploy and integrate informatics into their research and clinical practice, and (iii) facilitates interactions and collaborations among basic, translational and clinical scientists through efficient data exchange, sharing and knowledge engineering afforded by a user friendly informatics infrastructure. To meet these challenges, the BIC is leveraging resources and people in a variety of disciplines among UC, Argonne National Laboratory (ANL), the UC Hospitals (UCH), and the Biological Sciences Division (BSD). Activities are coordinated through the Initiative in Biomedical Informatics (iBi).

Three ongoing projects of interest are ...

Collaborator Finder

While researchers may be able to identify potential opportunities for collaboration with colleagues at other institutions, they are often not as well aware of potential collaborators among colleagues at their own institution. To address this problem, Informatics Core Co-leader Yves Lussier, M.D. and Information Systems Director Don Saner are developing and validating a Collaborator Finder that allows users to identify which University of Chicago faculty publish on topics most closely related to their own research. The current implementation uses a joint network and information theory analysis based on National Library of Medicine medical subject headings (MeSH) terms of all faculty members’ publications. It provides a list of University of Chicago faculty whose publications’ MeSH terms most closely match those of the user’s own publications (temporarily restricted to Department of Medicine faculty). To enhance the power of this system, the Collaborator Finder will also incorporate natural language processing to analyze the publications themselves, grant abstracts from the Computer Retrieval of Information on Scientific Projects (CRISP) database, and any other text investigators wish to provide (e.g., descriptions of ongoing projects or even rough ideas), then perform the networking analysis using all this information for all University of Chicago investigators. This approach differs from and complements that of BiomedExperts by Collexis in that connections are analyzed on the basis of research content rather than co-authorship. For an example, click here to see Collaborator Finder results for ITM Director Julian Solway, M.D. The system is currently undergoing evaluation but may develop into a useful tool that could be implemented by individual CTSA sites and possibly across all CTSA sites.

Translational Mart (TraM)

Translational research data are typically stored in heterogeneous databases, segregated, and described with inconsistent terminologies. Such inconsistency and fragmentation of data significantly impedes the efficiency of tracking and analyzing human-centered records. To address this problem, we have developed a data repository and management system named TraM, based on a domain ontology integrated entity relationship model. The TraM system has the flexibility to recruit dynamically evolving domain concepts and the ability to support data integration for a broad range of translational research. TraM relies on a semi-automated mechanism to standardize and restructure source data for data integration. The web-based application interfaces of TraM allow curators to improve data quality and provide robust and user-friendly cross-domain query functions. Data from 33,290 individuals under 22 IRB approved protocols belonging to several translational research projects have been used to assess TraM. This abstract is from: Wang, et al. Translational Integrity and Continuity: Personalized Biomedical Data Integration. J Biomed Inform. 2008 Aug 12. [Epub ahead of print]. PMID: 18760382

Service-oriented-architecture (SOA)/Grid-based Data Sharing
The University of Chicago and Argonne National Laboratory teams are part of the core team of developers for caGRID, the underpinning architecture for CaBIG, and serve as a Knowledge Center for caGRID https://cabig-kc.nci.nih.gov/CaGrid/KC. In concert with this, the University of Chicago’s Comprehensive Cancer Center has also committed to setup a CaBIG grid node (for data sharing). The Initiative in Biomedical Informatics (iBi) grid project with TraM, partially supported by the CTSA Informatics budget, will also build proof of concept systems in sharing data across institutional borders. The SOA project of Chicago Biomedicine Information Systems (clinical and research operations), in concert with iBi/CTSA, is an important project on internal cross-border data-sharing. Bridging SOA and grid will, in time, be an essential component of our architecture.