Graph Transformation in Molecular Biology

Rosselló, Francesc; Valiente, Gabriel

doi:10.1007/978-3-540-31847-7_7

Cited by 25 publications

(13 citation statements)

References 64 publications

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“…The string-based L-system was generalized to a parallel graph grammar by Culik and Lindenmayer [8] for modelling multi-cellular organisms. Graph grammars have then been used actively in biology [9], [10], [11]. In addition to the extensive use in biology, L-systems and graph grammars are also used in non-biological applications [12].…”

Section: A Backgroundmentioning

confidence: 99%

A graph model and grammar for multi-scale modelling using XL

Ong

Kurth

2012

2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops

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A graph formalism and grammar suitable for multiscale modelling is introduced in this paper. Existing rule-based rewriting mechanisms related to L-systems do not take scales into account or rely on string-based mechanisms. This poses difficulties to develop multi-scale models using rule-based graph approaches. Using a type graph to capture scale relationships and accounting for scales using an additional edge type, we introduce a technique to overcome these problems. Syntax for expressing multi-scale graphs allows the construction of models in the language XL coupled with existing rule-based functionality.

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Section: A Backgroundmentioning

confidence: 99%

A graph model and grammar for multi-scale modelling using XL

Ong

Kurth

2012

2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops

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“…Alternative approaches to graph rewriting in the context of (artificial) chemistry have been based on the single pushout (SPO) model of graph transformations, see e.g. [11,12]. We briefly discuss the rather technical difference between the DPO and SPO framework in Appendix A, where we also briefly outline our reasons for choosing DPO.…”

Section: Graph Grammars and Rule Compositionmentioning

confidence: 99%

Inferring chemical reaction patterns using rule composition in graph grammars

et al. 2013

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Background: Modeling molecules as undirected graphs and chemical reactions as graph rewriting operations is a natural and convenient approach to modeling chemistry. Graph grammar rules are most naturally employed to model elementary reactions like merging, splitting, and isomerisation of molecules. It is often convenient, in particular in the analysis of larger systems, to summarize several subsequent reactions into a single composite chemical reaction.Results: We introduce a generic approach for composing graph grammar rules to define a chemically useful rule compositions. We iteratively apply these rule compositions to elementary transformations in order to automatically infer complex transformation patterns. As an application we automatically derive the overall reaction pattern of the Formose cycle, namely two carbonyl groups that can react with a bound glycolaldehyde to a second glycolaldehyde. Rule composition also can be used to study polymerization reactions as well as more complicated iterative reaction schemes. Terpenes and the polyketides, for instance, form two naturally occurring classes of compounds of utmost pharmaceutical interest that can be understood as "generalized polymers" consisting of five-carbon (isoprene) and two-carbon units, respectively. Conclusion: The framework of graph transformations provides a valuable set of tools to generate and investigate large networks of chemical networks. Within this formalism, rule composition is a canonical technique to obtain coarse-grained representations that reflect, in a natural way, "effective" reactions that are obtained by lumping together specific combinations of elementary reactions.

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“…The use of Graph Transformation for biological systems has a long history, as pointed out in the overview paper [9], but early applications were mostly devoted to the field of morphogenesis. Our approach focuses on biochemistry, a field which gained much importance in the last decades because of the growth of biotechnology.…”

Section: Related Workmentioning

confidence: 99%

Molecular Analysis of Metabolic Pathway with Graph Transformation

Ehrig

Heckel

Lajios

2006

Lecture Notes in Computer Science

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Abstract. Metabolic pathway analysis is one of the tools used in biology and medicine in order to understand reaction cycles in living cells. A shortcoming of the approach, however, is that reactions are analysed only at a level corresponding to what is known as the 'collective token view' in Petri nets, i.e., summarising the number of atoms of certain types in a compound, but not keeping track of their identity. In this paper we propose a refinement of pathway analysis based on hypergraph grammars, modelling reactions at a molecular level. We consider as an example the citric acid cycle, a classical, but non-trivial reaction for energy utilisation in living cells. Our approach allows the molecular analysis of the cycle, tracing the flow of individual carbon atoms based on a simulation using the graph transformation tool AGG.

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Graph Transformation in Molecular Biology

Cited by 25 publications

References 64 publications

A graph model and grammar for multi-scale modelling using XL

A graph model and grammar for multi-scale modelling using XL

Inferring chemical reaction patterns using rule composition in graph grammars

Molecular Analysis of Metabolic Pathway with Graph Transformation

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