Article,
Data integration and genomic medicine
Journal of Biomedical Informatics, (February 2007)
DOI: 10.1016/j.jbi.2006.02.007
Abstract
Genomic medicine aims to revolutionize health care by applying our
growing understanding of the molecular basis of disease. Research
in this arena is data intensive, which means data sets are large
and highly heterogeneous. To create knowledge from data, researchers
must integrate these large and diverse data sets. This presents daunting
informatic challenges such as representation of data that is suitable
for computational inference (knowledge representation), and linking
heterogeneous data sets (data integration). Fortunately, many of
these challenges can be classified as data integration problems,
and technologies exist in the area of data integration that may be
applied to these challenges. In this paper, we discuss the opportunities
of genomic medicine as well as identify the informatics challenges
in this domain. We also review concepts and methodologies in the
field of data integration. These data integration concepts and methodologies
are then aligned with informatics challenges in genomic medicine
and presented as potential solutions. We conclude this paper with
challenges still not addressed in genomic medicine and gaps that
remain in data integration research to facilitate genomic medicine
