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    基于TGG的SBML与其他生物建模语言间的自动转换研究

    TGG Based Automatic Transformation Between SBML and Other Biological Modeling Languages

    • 摘要: 基于XSLT技术的SBML与其他生物建模语言之间的转换方法存在无法保证转换结果的确定性、语法正确性及不能满足模型转换的工业化需求等缺陷.针对以上问题,提出了利用图文法定义SBML Schema及其他生物建模语言,并且利用Triple Graph Grammar构造SBML与其他建模语言之间的转换方法.在此基础上,提出了一种基于单路径尝试条件的转换算法,该算法具有多项式时间复杂性,能够保证转换目标对象的确定性与语法正确性,给出了相关证明,并且讨论了该条件在生物模型转换中的适用性.与传统方法相比,该方法利用可视化方法实现转换,简化了定义过程;无需动态检查转换过程,只要转化规则正确即可保证转换结果正确;同时支持扩增传播以及模型间双向转换.最后,通过Petri网与SBML之间的转换例子证实了该算法的正确性与有效性.

       

      Abstract: XSLT based transformation, between SBML and other biological modeling languages, cannot describe comprehensive context-sensitive semantic correspondences among the inner elements of biological modeling objects; cannot guarantee the determinacy and syntactic correctness of transformation results; and also cannot meet industrial transformation requirements. Toward these problems, a triple graph grammar (TGG) based transformation method is presented, which utilizes graph grammars to define SBML schema and other biological modeling languages, and utilizes TGG to construct transformation between them. On this basis, a transformation algorithm is presented, which has polynomial time complexity and can guarantee determinacy and syntactic correctness. Compared with the traditional transformation between SBML and other biological modeling languages, the method in this paper has the following characteristics: 1) It utilizes context-sensitive grammar and has strong description capability; 2) It imposes graph-based approach to simplify transformation definition process; 3) It only needs static analysis of transformation rules at the design time without exploring dynamic analysis, because validation must be achieved if transformation rules satisfy some constraints; 4) It only requires to change direction of transformation rules to implement bi-directional transformation, without modifying any element; and 5) It supports incremental change propagation, since it preserves the correspondence information between source and target objects. Finally, correctness and effectiveness of this method are verified through an example of transformation between Petri net and SBML.

       

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