Translational integrity and continuity: Personalized biomedical data integration

  • Authors:

  • Xiaoming Wang;Lili Liu;James Fackenthal;Shelly Cummings;Oluwatobi I. Olopade;Kisha Hope;Jonathan C. Silverstein;Olufunmilayo I. Olopade

  • Affiliations:

  • Biomedical Informatics Core, Computation Institute, University of Chicago, 950 E 61st Street, Room 334, Chicago, IL 60637, USA and Computation Institute, University of Chicago, 5801 S Ellis Avenue ...;Biomedical Informatics Core, Computation Institute, University of Chicago, 950 E 61st Street, Room 334, Chicago, IL 60637, USA and Computation Institute, University of Chicago, 5801 S Ellis Avenue ...;Center for Clinical Cancer Genetics, Department of Medicine, University of Chicago, 5841 South Maryland Avenue, Room I-216, Chicago, IL 60637, USA;Center for Clinical Cancer Genetics, Department of Medicine, University of Chicago, 5841 South Maryland Avenue, Room I-216, Chicago, IL 60637, USA;Center for Clinical Cancer Genetics, Department of Medicine, University of Chicago, 5841 South Maryland Avenue, Room I-216, Chicago, IL 60637, USA;Center for Clinical Cancer Genetics, Department of Medicine, University of Chicago, 5841 South Maryland Avenue, Room I-216, Chicago, IL 60637, USA;Biomedical Informatics Core, Computation Institute, University of Chicago, 950 E 61st Street, Room 334, Chicago, IL 60637, USA and Computation Institute, University of Chicago, 5801 S Ellis Avenue ...;Center for Clinical Cancer Genetics, Department of Medicine, University of Chicago, 5841 South Maryland Avenue, Room I-216, Chicago, IL 60637, USA

  • Venue:
  • Journal of Biomedical Informatics
  • Year:
  • 2009

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Abstract

Translational research data are generated in multiple research domains from the bedside to experimental laboratories. These data are typically stored in heterogeneous databases, held by segregated research domains, 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 (http://tram.uchicago.edu), 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. The web-based application interfaces of TraM allow curators to improve data quality and provide robust and user-friendly cross-domain query functions. In its current stage, TraM relies on a semi-automated mechanism to standardize and restructure source data for data integration and thus does not support real-time data application.