Scientific data of importance to biologists in the Humitn Genome Project resides not only in conventional da.tabases, but in structured files maintained in a number of different formats (e.g. ASN.1 a.nd ACE) as well a.s sequence analysis packages (e.g. BLAST and FASTA). These formats and packages contain a number of data types not found in conventional databases, such as lists and variants, and may be deeply nested. We present in this paper techniques for querying and transforming such data, and illustrate their use in a prototype system developed in conjunction with the Human Genome Center for Chromosome 22. We also describe optimizations performed by the system, a crucial issue for bulk data.
Peter Buneman, Susan B. Davidson, Kyle Hart, G. Ch