Identifying, Interpreting, and Communicating Changes in XML-encoded Models of Biological Systems

Research in systems biology enhanced our knowledge of biological environments. Many discoveries are recorded in computational models which encode the structure of biological networks, and describe their temporal and spatial behavior. Due to tremendous efforts by the research community, the number of openly available models is numerous and still continually increasing [1]. To support the sharing of models and, thus, the reuse of research results, repositories such as the BioModels Database [2] and the Cellml Model Repository [3] collect and store models in exchangeable formats such as the Systems Biology Markup Language (SBML, [4]), or CellML [5]. Since only accessible models can be reused, such repositories are essential to guarantee transparent research. However, model repositories to date lack sufficient mechanisms to track the updates of models in their databases [6]. Model versions often cannot be addressed unambiguously and changes occurring between versions of a model are not communicated transparently. Therefore, a framework to identify the differences between models and their versions is a fundamental requirement to compare and combine models. Only with difference detection at hand users are able to grasp a model’s history and to identify errors and inconsistencies.