Structure, function, and behaviour of computational models in systems biology

Knüpfer, Christian; Beckstein, Clemens; Dittrich, Peter; Novère, Nicolas Le

doi:10.1186/1752-0509-7-43

Cited by 17 publications

(22 citation statements)

References 27 publications

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“…11 For cardiac metabolism, the currently practiced modeling approaches can be broadly subdivided into statistical, stoichiometric, and kinetic approaches. Multivariate statistical analyses of genomewide “–omics” data sets, although providing only marginal insight into the regulation of metabolic networks, are useful for the identification of metabolic markers for the presence and severity of specific heart diseases.…”

Section: Systems Biology and Mathematical Modeling Of Cardiac Metabolismmentioning

confidence: 99%

Assessing Cardiac Metabolism

Taegtmeyer¹,

Young²,

Lopaschuk³

et al. 2016

Circulation Research

237

147

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In a complex system of interrelated reactions, the heart converts chemical energy to mechanical energy. Energy transfer is achieved through coordinated activation of enzymes, ion channels, and contractile elements, as well as structural and membrane proteins. The heart’s needs for energy are difficult to overestimate. At a time when the cardiovascular research community is discovering a plethora of new molecular methods to assess cardiac metabolism, the methods remain scattered in the literature. The present statement on “Assessing Cardiac Metabolism” seeks to provide a collective and curated resource on methods and models used to investigate established and emerging aspects of cardiac metabolism. Some of those methods are refinements of classic biochemical tools, whereas most others are recent additions from the powerful tools of molecular biology. The aim of this statement is to be useful to many and to do justice to a dynamic field of great complexity.

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Section: Systems Biology and Mathematical Modeling Of Cardiac Metabolismmentioning

confidence: 99%

Assessing Cardiac Metabolism

Taegtmeyer¹,

Young²,

Lopaschuk³

et al. 2016

Circulation Research

237

147

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“…A number of approaches exist to compare models based on the encoding format, the XML tags, or semantic annotations. It is, for example, interesting to study models regarding function, structure and behavior [46]; regarding their temporal evolution [47,48]; or regarding their dynamics [49]. In this paper, we propose a first step towards to a new structural analysis by providing a workflow to retrieve frequent patterns.…”

Section: Discussionmentioning

confidence: 99%

Finding patterns in biochemical reaction networks

Henkel¹,

Lambusch²,

Sandkuhl³

et al. 2016

Preprint

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Background: Computational models in biology encode molecular and cell biological processes. These models often can be represented as biochemical reaction networks. Studying such networks, one is mostly interested in systems that share similar reactions and mechanisms. Typical goals of an investigation include understanding of the parts of a model, identification of reoccurring patterns, and recognition of biologically relevant motifs. The large number and size of available models, however, require automated methods to support researchers in achieving their goals. Specifically for the problem of finding patterns in large networks only partial solutions exist. Results:We propose a workflow that identifies frequent structural patterns in biochemical reaction networks encoded in the Systems Biology Markup Language. The workflow utilises a subgraph mining algorithm to detect frequent network patterns. Once patterns are identified, the textual pattern description can automatically be converted into a graphical representation. Furthermore, information about the distribution of patterns among the selected set of models can be retrieved. The workflow was validated with 575 models from the curated branch of BioModels. In this paper, we highlight interesting and frequent structural patterns. Further, we provide exemplary patterns that incorporate terms from the Systems Biology Ontology. Our workflow can be applied to a custom set of models or to models already existing in our graph database MaSyMoS. Conclusions:The occurrences of frequent patterns may give insight into the encoding of central biological processes, evaluate postulated biological motifs, or serve as a similarity measure for models that share common structures.Availability: https://github.com/FabienneL/BioNet-Mining

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“…Such diversity of substrates for common energy source production predispose to several concepts: (1) myocardial metabolism is very adaptive to organism condition and substrate environment and can vary between main energy resources; unfortunately, in heart failure this flexibility is mostly lost; (2) myocardial metabolism is a self-regulated mechanism; all the intermediates of the tricarboxylic acid cycle are mediators, controlling the main metabolic path and intensity of energy production (Randle cycle); (3) metabolites can be used as components for cell structure resynthesis, and, at the same time, cellular structures could be used as an energetic substrate; (4) metabolic dysfunction and accumulation of metabolites can damage cellular proteins and change the form and function of contractile filaments; (5) myocardial metabolism is not "intracellular chemistry"; this is a functional system, which is presented with specific structure and mediator mechanisms, assessing adaptation of cardiomyocytes to environmental variations [76,171].…”

Section: Metabolism In the Adult Healthy Heartmentioning

confidence: 99%

Myocardial Metabolism

Олейников¹

2019

Veterinary Anatomy and Physiology

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Myocardial metabolism alterations are associated with myocardial dystrophy and lead to the heart chambers dilatation, decreased contractility, organs perfusion and depended on symptoms. Nowadays heart failure treatment in veterinary medicine includes neurohormonal, circulatory and contractile aspects of this pathological state. Unfortunately, energy supplying component not presented in modern recommendations. Most of the used medications changing contractile ability, through the control of myocardial filaments sensibility to the different ions, but don't affect the ability of cardiomyocytes to produce enough energy for this work. In order to understand the heart failure syndrome more completely, we should elucidate features, characteristics, and interactions between components of myocardial energy supply.

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Structure, function, and behaviour of computational models in systems biology

Cited by 17 publications

References 27 publications

Assessing Cardiac Metabolism

Assessing Cardiac Metabolism

Finding patterns in biochemical reaction networks

Myocardial Metabolism

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