The Genome Data Base will be acquiring genetic and physical mapping data from a multiplicity of independent sources. It can be expected that labs mapping the same chromosome will have a wide variety of information in any given region. Automated methods will be developed to merge these sources of information, detect areas of conflict, and form a "consensus map". The map integration problem can be divided into two areas: defining the minimum set of attributes which permit efficient integration of map objects, and the development of likelihood estimates for determining the probability of the resultant maps. Analytical and data visualization tools will be developed for statistically characterizing integrated maps. Such characterizations will include more than just the "best" possible map. They will also indicate the statistical confidence to be placed in the assembled map, as well as the relative likelihood of this final map versus other nearby contenders. In the coming years, as GDB's role evolves from a data repository to a tool for the integration of genomic maps, low level map information will need to be stored in the database. The method of storage will be designed with the map integration process in mind, so that it can be performed with maximum efficiency, even with the rapid growth of the underlying data set. The objectives of the proposed study are: . The development of data structures for storing genomic map information. . The development of tools for collection, entry, retrieval, display, analysis, and dissemination of map information. . The study of map integration, including the definition of the minimum set of map object attributes which permit efficient integration and the use of likelihood estimates in the integration process.