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The Graph Grammar Library - A Generic Framework for Chemical Graph Rewrite Systems

Authors: Martin Mann; Heinz Ekker; Christoph Flamm;

The Graph Grammar Library - A Generic Framework for Chemical Graph Rewrite Systems

Abstract

Graph rewrite systems are powerful tools to model and study complex problems in various fields of research. Their successful application to chemical reaction modelling on a molecular level was shown but no appropriate and simple system is available at the moment. The presented Graph Grammar Library (GGL) implements a generic Double Push Out approach for general graph rewrite systems. The framework focuses on a high level of modularity as well as high performance, using state-of-the-art algorithms and data structures, and comes with extensive documentation. The large GGL chemistry module enables extensive and detailed studies of chemical systems. It well meets the requirements and abilities envisioned by Yadav et al. (2004) for such chemical rewrite systems. Here, molecules are represented as undirected labeled graphs while chemical reactions are described by according graph grammar rules. Beside the graph transformation, the GGL offers advanced cheminformatics algorithms for instance to estimate energies ofmolecules or aromaticity perception. These features are illustrated using a set of reactions from polyketide chemistry a huge class of natural compounds of medical relevance. The graph grammar based simulation of chemical reactions offered by the GGL is a powerful tool for extensive cheminformatics studies on a molecular level. The GGL already provides rewrite rules for all enzymes listed in the KEGG LIGAND database is freely available at http://www.tbi.univie.ac.at/software/GGL/.

Extended version of an abstract published in proceedings of the International Conference on Model Transformation (ICMT) 2013

Countries
Austria, Germany
Keywords

FOS: Computer and information sciences, 104022 Theoretical chemistry, Molecular Networks (q-bio.MN), Biomolecules (q-bio.BM), 102004 Bioinformatik, Computational Engineering, Finance, and Science (cs.CE), Quantitative Biology - Biomolecules, 104022 Theoretische Chemie, FOS: Biological sciences, Computer Science - Mathematical Software, Quantitative Biology - Molecular Networks, 102004 Bioinformatics, Computer Science - Computational Engineering, Finance, and Science, Mathematical Software (cs.MS)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Average
Top 10%
Green