The exponential growth in the volume of information available on molecular structures and cellular function demands new modeling methodologies. Such methodologies should integrate in one framework information on genetic sequence polymorphisms, along with their structural, functional, and dynamic/behavioral consequences, including disease phenotypes. We propose a graphical knowledge model for representing molecular functional information as a first step towards modeling the relationship between molecular structure and disease phenotypes. Our application domain is the role of tRNA molecules in translation and translation-related disease. tRNA constitutes a good test-bed because there exists rich literature on tRNA molecular structure as well as the diseases that result from abnormal structures. Our model combines the best aspects of three existing models: (1) a Workflow model that can be mapped to Petri Nets, which hierarchically specifies processes, their participating molecular structures, and the functional roles that those participants play, (2) Transparent Access to Multiple Biological Information Sources, which serves as a controlled biological terminology, and (3) Unified Medical Language System, which serves as a controlled medical terminology. The formal basis of our model enables answering queries to understand the compositional properties of molecular ensembles, and to present the relationship between a defective process or clinical phenotype to the mutation that is causing it. The Petri Net representation enables verifying boundedness and soundness as well as answering reachability questions, which in the context of biological systems, may aid in predicting system behavior in the presence of dysfunctional processes, functions, or structural components. Our model is available at http://mis.hevra.haifa.ac.il/~morpeleg/ Keywords: knowledge model, ontology, Workflow, Petri Net, mutation, biological process
