We report on a knowledge-based pathway-finding system that builds on the cell-signaling networks database, CSNDB, which we developed previously. This new system, PaF-CSNDB, uses a general inference engine to apply rules for finding and coupling pathways between or around specific biomolecules from the CSNDB database. We show how PaF-CSNDB finds relationships in a large but fragmented collection of cell-signaling knowledge by filtering out and composing together those sections of pathways specified from an extensive and complex set of binary or pair-wise cell-signaling reactions.
|Number of pages||18|
|Journal||In silico biology|
|Publication status||Published - 1999|
ASJC Scopus subject areas
- Molecular Biology
- Computational Mathematics
- Computational Theory and Mathematics