A knowledge based approach for representing and reasoning about signaling networks

• DOI: 10.1093/bioinformatics/bth918
• Publication Date: 2004-07-19T17:07:37Z
• Authors: C. Baral; K. Chancellor; N. Tran; N.L. Tran; A. Joy; M. Berens
• Keywords: 0303 health sciences; 03 medical and health sciences; Proteome; Artificial Intelligence; Gene Expression Profiling; Gene Expression; Computer Simulation; Models, Biological; Algorithms; Signal Transduction

In this paper we propose to use recent developments in knowledge representation languages and reasoning methodologies for representing about signaling networks. Our approach is different from most other qualitative systems biology approaches that it based on (or inferencing) rather than simulation. Some of the advantages our are, can advances with incomplete partial information deal gaps signal network knowledge; perform various kinds such as planning, hypothetical explaining observations.Using have developed system BioSigNet-RR We a NFkappaB related pathway illustrate currently do.The available Web at http://www.public.asu.edu/~cbaral/biosignet