caa a22 4500 463186958 CHVBK 20180406164856.0 cr unu---uuuuu 170326e20071201xx s 000 0 eng 10.1007/s10472-008-9091-8 doi (NATIONALLICENCE)springer-10.1007/s10472-008-9091-8 Reasoning about non-immediate triggers in biological networks [Elektronische Daten] [Nam Tran, Chitta Baral] Modeling molecular interactions in signalling networks is important from various perspectives such as predicting side effects of drugs, explaining unusual cellular behavior and drug and therapy design. Various formal languages have been proposed for representing and reasoning about molecular interactions. The interactions are modeled as triggered events in most of the approaches. The triggering of events is assumed to be immediate: once an interaction is triggered, it should occur immediately. Although working well for engineering systems, this assumption poses a serious problem in modeling biological systems. Our knowledge about biological systems is inherently incomplete, thus molecular interactions are constantly elaborated and refined at different granularity of abstraction. The model of immediate triggers can not consistently deal with this refinement. In this paper we propose an action language to address this problem. We show that the language allows for refinements of biological knowledge, although at a higher cost in terms of complexity. Springer Science+Business Media B.V., 2008 Molecular interaction networks nationallicence Knowledge-based modeling nationallicence Causality nationallicence Tran Nam Department of Pathology, Yale School of Medicine, Yale University, 06510, New Haven, CT, USA aut Baral Chitta Computer Science and Engineering, School of Computing & Informatics, Arizona State University, 85281, Tempe, AZ, USA aut Annals of Mathematics and Artificial Intelligence Springer Netherlands 51/2-4(2007-12-01), 267-293 1012-2443 51:2-4<267 2007 51 10472 https://doi.org/10.1007/s10472-008-9091-8 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10472-008-9091-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Tran Nam Department of Pathology, Yale School of Medicine, Yale University, 06510, New Haven, CT, USA aut NATIONALLICENCE 700 1- Baral Chitta Computer Science and Engineering, School of Computing & Informatics, Arizona State University, 85281, Tempe, AZ, USA aut NATIONALLICENCE 773 0- Annals of Mathematics and Artificial Intelligence Springer Netherlands 51/2-4(2007-12-01), 267-293 1012-2443 51:2-4<267 2007 51 10472 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer