Biologists currently devote significant time and effort searching information for their research. The wide diversity in terminology used inhibit effective computerized and manual data retrieval. For example, say a user wants to find all the gene products that are involved in bacterial protein synthesis, and that have sequences or structures significantly different from those in humans. If one database describes these molecules as being involved in ‘translation’, whereas another uses the phrase ‘protein synthesis’, it will be difficult for the user - and even harder for a computer - to find functionally equivalent terms. A schema mapping tool, which interprets results from one database in terminology used by a second database, can solve such problems. We started our project by developing schema mapping for UniProt1 and Genbank2 protein resources, both of which can be rendered in XML format, as a large part of scientific community uses proteomic resources. The approach will...