Given the diversity of biological information, we strongly believe
that a retrieval system can perform better by integrating the links
that exist between biological databases covering different areas
and different types of data. As biologists identify new genes and
gene functions every day, new sequences are stored and new
literature is published at an increasing speed. The size of
nucleotide sequences databases such as GenBank is growing
larger as well as the size of protein sequences, protein structures
and biomedical articles databases. The data is often structured
and organized according to a project covering a specific area, e.g.
a specific model organism. It is therefore difficult for biologists
to find information that is not directly related to their field of
research. Fortunately, much work was done on linking the
various databases by annotating the records with references to
external database records. These records and links form a
complex graph that takes a lot of time and effort for users to
navigate and search. Anybody who has searched the web is
familiar with the frustrating experience of pursuing links,
backtracking, and returning to the search engine to reformulate
the query and begin again. We clearly need to find better ways
to search and navigate the biological information in an integrated
fashion.