Reasoning about non-immediate triggers in biological networks |
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Authors: | Nam Tran Chitta Baral |
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Affiliation: | (1) Department of Pathology, Yale School of Medicine, Yale University, New Haven, CT 06510, USA;(2) Computer Science and Engineering, School of Computing & Informatics, Arizona State University, Tempe, AZ 85281, USA |
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Abstract: | 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.
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Keywords: | Molecular interaction networks Knowledge-based modeling Causality |
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