Annotation and merging of SBML models with semanticSBML

Krause, Falko; Uhlendorf, Jannis; Lubitz, Timo; Schulz, Marvin; Klipp, Edda; Liebermeister, Wolfram

doi:10.1093/bioinformatics/btp642

Cited by 94 publications

(98 citation statements)

References 7 publications

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“…For example, a number of models of intracellular calcium metabolism were discovered. It would be worthwhile developing one of these models further to include Vitamin D metabolism, especially as Vitamin D is essential for calcium absorption [92], with its physiological optimum defined by the amount required to maintain calcium levels and prevent secondary hyperparathyroidism [93]. Therefore, a computer model could help to investigate the long-term impact of vitamin D deficiency on calcium metabolism.…”

Section: Discussionmentioning

confidence: 99%

Nutrition Research and the Impact of Computational Systems Biology

Auley¹

2013

J Comput Sci Syst Biol

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The value of computational modelling in improving our understanding of complex nutrient-based pathways is becoming increasingly recognised. This is due to the integral role that computer modelling is playing within the multidisciplinary field of systems biology, where in silico quantitative simulations are being used to compliment more traditional wet-laboratory investigations. A large number of computational models are accessible via the Biomodels database, an archive of openly available peer reviewed models of biological systems. Moreover, there has been an explosion in the availability of free modelling software tools that can be used to assemble and simulate the dynamic behaviour of nutrient mediated systems. Computational modelling will continue to play an increasingly significant role in nutrition research. Thus, it is important that freely accessible models and resources relevant to nutrition research are highlighted. In response to these needs, we firstly examined the Biomodels database, to identify and categorise nutrition themed models. The outcome of the analysis revealed 163 nutrition themed models. These models are mainly cellular in nature, with intracellular representations of calcium oscillations the most common. Secondly, a generic nutrition centred modelling framework was used, to explore recent advances, data repositories and software relevant to model building. We conclude this paper by using our review findings to discuss areas of nutrition that could further exploit the potential of computational modelling in the future. As a result of the progress in nutrient centred systems modelling it is important that freely available models, approaches, software and data resources relevant to nutrient focused modelling are highlighted. As a result of these needs, the aim of this paper is to discuss the progress in systems modelling and its relevance to nutrition research. Firstly, we will briefly introduce the main modelling approaches. We then highlight openly accessible nutrient themed models archived within the Biomodels database http://www.ebi.ac.uk/biomodels-main/ a repository for published peer reviewed models [22]. These models have been encased within the System Biology Markup Language (SBML) http://sbml.org/Main_Page a format used for model exchange [23]. We recognise that several formats exist for exchanging computational models, including the Cell Mark-up language (Cell-ML) [24] and the recently developed simulation experiment description markup language (SED-ML) [25], which also supports SBML. However, the rationale for focusing on SBML is because it is currently the leading exchange format in Systems Biology. This is emphasized by the results of a search of PubMed and Biomodels for models or tools published in each year since SBML was launched in 2003. The search terms SBML/ systems biology markup language were used to search for publications archived in PubMed. Biomodels was then used to crosscheck for models not revealed by the PubMed search. Figure 1 provides a summary of this ...

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Section: Discussionmentioning

confidence: 99%

Nutrition Research and the Impact of Computational Systems Biology

Auley¹

2013

J Comput Sci Syst Biol

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“…SemanticSBML [17] provides the state of the art tools to obtain a monolithic merged model starting from different IFMBE Proceedings Vol. 31 molecular pathways.…”

Section: Discussionmentioning

confidence: 99%

A Cross-Format Framework for Consistent Information Integration among Molecular Pathways and Ontologies

et al. 2010

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Abstract-The information coming from biomedical ontologies and runnable pathways is expanding continuously: research communities keep this process up and their advances are generally shared by means of dedicated resources published on the web. Having different objectives and different abstraction levels, most of these resources "speak" different languages. Employing an extensible collection of interpreters, we propose a system that abstracts the information from different resources and combines them together into a common meta-format. Preserving the resource independence, we provide an alignment service that can be used for multiple purposes. Two recent examples are: 1) The new web application Cytosolve uses an embedded version of this system to provide congruous parallel simulation of multiple models; 2) Using the BioModels.net database, a searchable dictionary of equivalent molecular reaction paths was built. Finally, the enriched knowledge can be exported in OWL and queried by semantically-enabled tools such as Protégé. In this approach, we see a valuable tool to integrate and test information originating from different sources, while preserving the independence of the model curation process.

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“…From the software tools surveyed, currently only Tools-4-Metatool (Xavier et al, 2011), Compare Subsystems (Oberhardt et al, 2011), SemanticSBML (Krause et al, 2010), COBRA (Becker et al, 2007), The FAME (Boele et al, 2012), MetRxn (Kumar et al, 2012), BudHat (Waltemath et al, 2013), PINT (Wang et al, 2010) and MEMOSys (Pabinger et al, 2011) provide functionality that is related to the comparison of models. Software tools mostly rely on internal or external identifiers, like KEGG ID and ChEBI ID and do not tolerate even small differences in metabolite names like brackets, quotes, apostrophes, spaces, upper/lower case letters and some more symbols which may be caused by the modelers style of defining metabolites.…”

Section: Current Approach Of Metabolic Model Comparisonmentioning

confidence: 99%

Comparative Analysis of Biochemical Network Reconstructions

Mednis¹

2016

BJMC

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Abstract. Reconstruction of genome-scale metabolic network is a result of assembling various information sources about all biochemical reactions expected in the metabolic network of interest. Despite the efforts of leading bio-models databases to make comparison of biochemical networks by elements names obsolete, interest from researchers in using string similarity metrics in comparison of metabolites names has been growing. Multiple challenges in comparison of reconstructions are discussed in this article and an insight into current approach of metabolic model comparison has been given. The discussion of challenges and attempts to solve them are followed by the author's proposed algorithm for models comparison that can be particularly useful in case of reconstructions. Special attention is given to the use of metabolites names and chemical formulas. The author's proposed algorithm has been implemented in a software tool ModeRator. The article is concluded with use cases of the comparison algorithm and the software tool.

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Annotation and merging of SBML models with semanticSBML

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 94 publications

References 7 publications

Nutrition Research and the Impact of Computational Systems Biology

Nutrition Research and the Impact of Computational Systems Biology

A Cross-Format Framework for Consistent Information Integration among Molecular Pathways and Ontologies

Comparative Analysis of Biochemical Network Reconstructions

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