The SBML ODE Solver Library: a native API for symbolic and fast numerical analysis of reaction networks

Machné, Rainer; Finney, Andrew; Müller, Stefan; Lu, James; Widder, Stefanie; Flamm, Christoph

doi:10.1093/bioinformatics/btl086

Cited by 85 publications

(58 citation statements)

References 5 publications

(3 reference statements)

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“…In studying biological model, we require solution for a given set of parameter values along with their examination for dependency towards other species in the model. SBML based ODE Solver (Funahashi et al 2003;Machné et al 2006) was used through CellDesigner, which enables us to run ODE-based simulations. ODE based simulations are preferred method for quantitative analysis as they surpass logical methods in term of computational efficiency, while considering species concentration and time as major parameters.…”

Section: Methodsmentioning

confidence: 99%

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A quantitative study of gene regulatory pathways in Bacillus subtilis for virulence and competence phenotype by quorum sensing

Kumar

Singh

2013

Syst Synth Biol

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Quorum sensing (QS) is a process which allows a population of bacteria to coordinately regulate gene expression of their entire community. Bacillus subtilis is a soil organism which uses QS to alternate between competence for DNA uptake and sporulation. We propose a model to describe the components involved in QS and to analyze reaction species involved in the regulation of QS machinery. We targeted only those QS phenotypes for which the genetic organization and molecular characterization of the components are fully elucidated. We have analyzed simulations for concentration of different species involved in competence as well as sporulation pathways at diverse time period using quantitative methods. It was observed that there is possibility of achieving different measurement from reactions taken place between species by applying irreversible Michaelis-Menten kinetic law. We obtain variation in measurement on changing parameters such as concentrations ranging from 0.3 to 50 lM in stepwise manner by setting end time in the range of 0.1-100 ms. Additionally we observe covariance between different reaction species involved in QS by fluctuating their quantities in real-time simulations. Our model mimics correctly the phenotype for competence and virulence. We concluded that time factor play major role to determine rate kinetics of diverse reaction species as compared to their concentrations and support the hypothesis of getting genetic stability while colonies are in synchronization.

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Section: Methodsmentioning

confidence: 99%

“…The SBML ODE Solver Library (SOSLib) is a C?? programming library for symbolic and numerical analysis of chemical reaction network models encoded in SBML (Machné et al 2006). The simulation engine itself is executed by the native library, and the results are shown in a GUI window written in Java.…”

Section: Methodsmentioning

confidence: 99%

A quantitative study of gene regulatory pathways in Bacillus subtilis for virulence and competence phenotype by quorum sensing

Kumar

Singh

2013

Syst Synth Biol

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“…Based on this information, users can manually extend their networks step by step. Simulations can be performed using external tools such as Copasi [11] and other ODE solvers [12].…”

Section: Related Workmentioning

confidence: 99%

VANESA - A Software Application for the Visualization and Analysis of Networks in Systems Biology Applications

Brinkrolf

Janowski

Kormeier

et al. 2014

Journal of Integrative Bioinformatics

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SummaryVANESA is a modeling software for the automatic reconstruction and analysis of biological networks based on life-science database information. Using VANESA, scientists are able to model any kind of biological processes and systems as biological networks. It is now possible for scientists to automatically reconstruct important molecular systems with information from the databases KEGG, MINT, IntAct, HPRD, and BRENDA. Additionally, experimental results can be expanded with database information to better analyze the investigated elements and processes in an overall context. Users also have the possibility to use graph theoretical approaches in VANESA to identify regulatory structures and significant actors within the modeled systems. These structures can then be further investigated in the Petri net environment of VANESA. It is platform-independent, free-of-charge, and available at http://vanesa.sf.net. BackgroundOver the last decades of biomedical research, it has become apparent that a biological element can never be investigated in isolation, since the degree of regulation covers almost all omic levels. Cellular life is mostly a network of interacting elements [1], in which the biological elements, such as DNA, RNA, proteins, and metabolites interact with each other. Cellular life is complex, the investigation very time-consuming and experimental analysis quite complicated. Therefore, scientists mostly have only detailed information and broad knowledge about the main interaction partners. But a biological element or process is always a part of a larger machinery or regulatory process. Thus, natural scientists need reliable information about the involved elements and/or processes and standards for data storage and representation [2]. Furthermore, they need manageable biological networks presenting the whole context of regulation in order to produce good theoretical models, which can be used for hypothesis testing.One possibility for gaining additional knowledge and linking different datasets is by accessing knowledge from biological databases. Biological databases are large repositories storing relevant information. However, this kind of information is distributed over different autonomous and heterogeneous biological databases, which need to be collected, filtered, cleaned, normalized, and linked in complex and time-consuming processes. Actually, more than 1,500 biological databases covering various areas of biology can be found [3]. Although data integration

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“…We first present the dynamics of the seed closed reaction network when the initial amount of each molecular species is equal to 10, see Figure 6. This graph was obtained by solving the ODE system generated by the reaction network (in SBML format) using the SBML ODE solver (14).…”

Section: Evolving Closed Reaction Networkmentioning

confidence: 99%

CLOSURE IN ARTIFICIAL CELL SIGNALLING NETWORKS - Investigating the Emergence of Cognition in Collectively Autocatalytic Reaction Networks

Decraene

2009

Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing

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Abstract:Cell Signalling Networks (CSNs) are complex biochemical networks responsible for the coordination of cellular activities in response to internal and external stimuli. We hypothesize that CSNs are subsets of collectively autocatalytic reaction networks. The signal processing or cognitive abilities of CSNs would originate from the closure properties of these systems. We investigate how Artificial CSNs, regarded as minimal cognitive systems, could emerge and evolve under this condition where closure may interact with evolution. To assist this research, we employ a multi-level concurrent Artificial Chemistry based on the Molecular Classifier Systems and the Holland broadcast language. A critical issue for the evolvability of such undirected and autonomous evolutionary systems is to identify the conditions that would ensure evolutionary stability. In this paper we present some key features of our system which permitted stable cooperation to occur between the different molecular species through evolution. Following this, we present an experiment in which we evolved a simple closed reaction network to accomplish a pre-specified task. In this experiment we show that the signal-processing ability (signal amplification) directly resulted from the evolved systems closure properties.

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The SBML ODE Solver Library: a native API for symbolic and fast numerical analysis of reaction networks

Cited by 85 publications

References 5 publications

A quantitative study of gene regulatory pathways in Bacillus subtilis for virulence and competence phenotype by quorum sensing

A quantitative study of gene regulatory pathways in Bacillus subtilis for virulence and competence phenotype by quorum sensing

VANESA - A Software Application for the Visualization and Analysis of Networks in Systems Biology Applications

CLOSURE IN ARTIFICIAL CELL SIGNALLING NETWORKS - Investigating the Emergence of Cognition in Collectively Autocatalytic Reaction Networks

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