Affiliations: Computational Biology Research Center (CBRC), National
Institute of Advanced Industrial Science and Technology (AIST), 2-43 Aomi,
Koutou-ku, Tokyo 135-0064, Japan. E-mail: [email protected] | Institute for Bioinformatics Research and Development
(BIRD), Japan Science and Technology Agency (JST), 3-14-4 Shirokane-dai,
Minato-ku, Tokyo 108-0071, Japan. E-mail: [email protected] | Graduate School of Frontier Sciences, University of
Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba 277-8562, Japan. E-mail:
[email protected]
Note: [] Corresponding author
Abstract: An intelligent system for signal transduction pathways and other
higher order functional knowledge is presented. Molecular mechanisms of
biological processes are typically represented as diagrams ("pathways") that
have a graph-analogical network structure. However, due to the diversity of
topics that pathways cover, their constituent biological entities are highly
diverse and range from metal ion to protein to biological processes in general.
In addition, the kinds of interactions that connect biological entities are
likewise diverse. Consequently, current knowledge about pathways is highly
heterogeneous both in the sense of the types of constituents and the
granularity of descriptions. To cope with this problem, the proposed system
adopts a recursive and hierarchical representation model that enables the
annotation and query of pathways or sub-pathways of arbitral granularity. By
combining the use of this hierarchical structure and biological ontologies,
literature-based information regarding biological mechanisms becomes accessible
by computer.
Keywords: pathway database, ontology, signal transduction, textual knowledge
