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The exponential growth in the volume of biological information available makes it difficult for researchers to assemble the details into coherent models. Although an accurate model is ideal, full details are not generally available and are gained only incrementally. Therefore, as a first step toward integration of information, we propose a knowledge model for the qualitative representation of the relationships between mutations in genes and their effects at molecular cellular and clinical phenotypic levels. Our framework combines and extends two components: 1) a workflow model that allows hierarchical process and participant specifications; 2) Transparent Access to Multiple Bioinformatics Information Sources and the Unified Medical Language System, which serve as controlled biological and medical terminologies. By mapping our framework to Petri nets, we can perform qualitative simulations to validate models, and aid in predicting system behavior in the presence of dysfunctional components. This can be a step toward accurate quantitative models. Our application domain is the role of transfer ribonucleic acid molecules in protein translation-related disease. As an initial evaluation, we show that Petri nets derived from the historic and current views of the translation process yield different dynamic behavior. Our model is available at http://smi.stanford.edu/projects/helix/pubs/process-model/.