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Modelers of molecular signaling networks must cope with the combinatorial explosion of protein states generated by posttranslational modifications and complex formation. Rule-based models provide a powerful alternative to approaches that require explicit enumeration of all possible molecular species of a system. Such models consist of formal rules(More)
Many proteins are composed of structural and chemical features--"sites" for short--characterized by definite interaction capabilities, such as noncovalent binding or covalent modification of other proteins. This modularity allows for varying degrees of independence, as the behavior of a site might be controlled by the state of some but not all sites of the(More)
  • Samson Abramsky, Roger Hindley, P. Dybjer Gothenburg, T. Ehrhard Marseille, M. Hasegawa Kyoto, F. Honsell Udine +81 others
  • 2015
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This volume contains the papers presented at the Tenth International Workshop on Developments in Computational Models (DCM) held in Vienna, Austria on 13th July 2014, as part of the Vienna Summer of Logic. Several new models of computation have emerged in the last years, and many developments of traditional computational models have been proposed with the(More)
Rule-based modelling has already proved successful for taming the combinatorial complexity , typical of cellular signalling, caused by the combination of physical protein-protein interactions and modifications that may generate astronomical numbers of unique molecular species. However, traditional rule-based approaches, based on an unstructured space of(More)
Models will play a central role in the representation, storage, manipulation , and communication of knowledge in systems biology. Models capable of fulfilling such a role will likely differ from the familiar styles deployed with great success in the physical sciences. Molecular systems at the basis of cellular decision processes are concurrent and(More)
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