Abstract
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.
Original language | English |
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Pages (from-to) | 129-146 |
Number of pages | 18 |
Journal | In silico biology |
Volume | 1 |
Issue number | 3 |
Publication status | Published - 1999 |
ASJC Scopus subject areas
- Molecular Biology
- Genetics
- Computational Mathematics
- Computational Theory and Mathematics