This grant will provide support for the infrastructure of the molecular biology database research program at the evergreen State College over the next year, maintaining a full-time programmer for months and providing limited travel and software upgrading. Activities which will be enhanced by this support include: 1. Completion of publication of the analysis of the bacteriophage T4 genome. With its approximately 300 genes and long years of study, T4 is the most complex virus for which the entire sequence is known. Many interesting phenomena have already been observed, from both spliced- and folded-out introns to nested genes and complex protein machines to a 26-amino acid dual-function protein gene product to genes highly homologous with eukaryotic proteins. The computer support under this grant will facilitate interaction among the members of the T4 community, and also work with various outside groups using the T4 data set as a model system for genoming analysis. A major activity will be to explore available tools for analyzing the still-uncharacterized half of the genes involved in the transition from host to viral metabolism after infection by large virulent phages. This work will also help to identify the most useful candidate programs for a Molecular Biologist's Computational Workbench. 2. Support of collaborative efforts for object-oriented molecular biology database specification, research and prototype development. This collaboration involves the Evergreen team (Drs. Cushing and Kutter, Tom Stidham and several students), Tom Marr and colleagues at Cold Spring Harbor and Tim Hunkapillar and David Yee at the University of Washington. Here, the major current work involves development of a metadatabase for the storage of complex multiple database sequence comparisons, particularly important in facilitating comparing search results across a range of search programs to tease out weak but significant relationships from very large amounts of data . The metadatabase will be built upon the framework existing in the Genome Topographer, an integrated database for genomic analysis and viewing being developed by Tom Marr; we have been collaborating with them for the last year on its expansion to application to prokaryotic systems. In a parallel effort Tim Hunkapillar and David Yee will b implementing the sequence comparison metadatabase in Sybase so that these two database approaches can be compared in functionality and usability; we are working together closely on this project. 3. Provide support to students in the "Student Originated Software" and "Molecule to Organism" programs who are involved in the above projects. The infrastructure thus supported makes it possible for molecular biology and computer scientist faculty and students to work together, sharing problems and solutions in facilitating analysis of the complex ways that genomic information is organized and expressed.
