Abstract
MotivationMolecular interaction maps have emerged as a meaningful way of representing biological mechanisms in a comprehensive and systematic manner. However, their static nature provides limited insights to the emerging behaviour of the described biological system under different conditions. Computational modelling provides the means to study dynamic properties through in silico simulations and perturbations. We aim to bridge the gap between static and dynamic representations of biological systems with CaSQ, a software tool that infers Boolean rules based on the topology and semantics of molecular interaction maps built with CellDesigner.ResultsWe developed CaSQ by defining conversion rules and logical formulas for inferred Boolean models according to the topology and the annotations of the starting molecular interaction maps. We used CaSQ to produce executable files of existing molecular maps that differ in size, complexity and the use of Systems Biology Graphical Notation (SBGN) standards. We also compared, where possible, the manually built logical models corresponding to a molecular map to the ones inferred by CaSQ. The tool is able to process large and complex maps built with CellDesigner (either following SBGN standards or not) and produce Boolean models in a standard output format, Systems Biology Marked Up Language-qualitative (SBML-qual), that can be further analyzed using popular modelling tools. References, annotations and layout of the CellDesigner molecular map are retained in the obtained model, facilitating interoperability and model reusability.Availability and implementationThe present tool is available online: https://lifeware.inria.fr/∼soliman/post/casq/ and distributed as a Python package under the GNU GPLv3 license. The code can be accessed here: https://gitlab.inria.fr/soliman/casq.Supplementary information Supplementary data are available at Bioinformatics online.
Highlights
1.1 Biological network representations and molecular interaction mapsBiological phenomena can be viewed in the form of interaction networks where components are represented as ‘nodes’ and the interactions between components are represented as ‘edges’
Representing the complexity of biological regulatory systems using networks enables the analysis of their topology, identifying distinct clusters that may correspond to specific biological processes (‘modules’) and nodes with a high degree of connectivity (‘hubs’), exercising a significant influence on the propagation of biological information (Barabasi and Oltvai, 2004; Ideker and Nussinov, 2017; Zhang et al, 2014)
We present CaSQ (CellDesigner as Systems Biology Markup Language (SBML)-qual), a tool for automated inference of large-scale, parameter-free Boolean models, from molecular interaction maps with preliminary logic rules based on network topology and semantics
Summary
1.1 Biological network representations and molecular interaction maps. Biological phenomena can be viewed in the form of interaction networks where components (genes, proteins) are represented as ‘nodes’ and the interactions between components are represented as ‘edges’. Network interactions can be directed or undirected, depending on the biological information available that allows the characterization of the interaction (inhibition or activation) and the source and the target node. Representing the complexity of biological regulatory systems using networks enables the analysis of their topology, identifying distinct clusters that may correspond to specific biological processes (‘modules’) and nodes with a high degree of connectivity (‘hubs’), exercising a significant influence on the propagation of biological information (i.e. signal, regulation) (Barabasi and Oltvai, 2004; Ideker and Nussinov, 2017; Zhang et al, 2014).
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