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ABSTRACT:
It is widely appreciated that it is no longer possible for biomedical research scientists to keep up with as much of what is published in their field as they ought. One solution to this problem is to increase the efficiency of information use by moving away from the classical browsing model for scientific information dissemination towards an information on demand model which would allow researchers to access information quickly and efficiently only as they need it. Molecular biology databases have been proliferating rapidly. The analysis of genomic, molecular, cellular, and clinical data, and it thus offers a remarkable set of challenges to biomedical informatics. These include infrastructural challenges such as the creation of data models and databases for storing these data, the integration of these data with external databases, the extraction of information from natural language text, and the protection of databases with sensitive information. There are also scientific challenges in creating tools to support gene expression analysis, three-dimensional structural analysis, and comparative genomic analysis. The database heterogeneity and complexity pose a great challenge to efforts in database interoperation and metadata are necessary for performing database comparisons, include descriptions of primitive database objects and specification of correspondences among the database objects.
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