http://precedings.nature.com/tags/modelling Recently posted documents tagged with 'modelling' Nature Publishing Group en Nature Precedings http://precedings.nature.com/images/header_logo.gif http://precedings.nature.com http://dx.doi.org/10.1038/npre.2009.3724.1 Standard graphical representations have played a crucial role in science and engineering throughout the last century. Without electrical symbolism, it is very likely that our industrial society would not have evolved at the same pace. Similarly, specialized notations such as the Feynmann notation or the process flow diagrams did a lot for the adoption of concepts in their own fields. With the advent of Systems Biology, and more recently of Synthetic Biology, the need for precise and unambiguous descriptions of biochemical interactions has become more pressing. While some ideas have been advanced over the last decade, with a few detailed proposals, no actual community standard has emerged. The Systems Biology Graphical Notation (SBGN) is a graphical representation crafted over several years by a community of biochemists, modellers and computer scientists. Three orthogonal and complementary languages have been created, the Process Descriptions, the Entity Relationships and the Activity Flows. Using these three idioms a scientist can represent any network of biochemical interactions, which can then be interpreted in an unambiguous way. The set of symbols used is limited, and the grammar quite simple, to allow its usage ranging from textbooks and teaching in high schools to peer reviewed articles in scientific journals. The first level of the SBGN Activity Flow language has been publicly released. Shared by the communities of biochemists, genomic scientists, theoreticians and computational biologists, SBGN languages will foster efficient storage, exchange and reuse of information on signaling pathways, metabolic networks and gene regulatory maps. http://dx.doi.org/10.1038/npre.2009.3724.1 Mon, 07 Sep 2009 19:43:48 UTC Systems Biology Graphical Notation: Activity Flow language Level 1 doi:10.1038/npre.2009.3724.1 2009-09-07 Huaiyu Mi Nature Precedings 2009-09-07T19:43:48Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2008.2649.1 Acquiring a comprehensive understanding of the behaviour of carbon dioxide under reservoir conditions is essential for optimizing its usage in enhanced oil recovery (EOR) and for developing sequestration schemes. In order to obtain this understanding, it is necessary to study the physical properties and phase behaviour of mixtures of carbon dioxide with hydrocarbons and brines under conditions of high pressure. In this work we are addressing both the experimental and the theoretical aspects of this problem. A new apparatus, based on the static-analytical method, has been developed to measure phase equilibrium. The equipment comprises a high-pressure cell with sapphire windows for visual observation and phase sampling, with on-line gas chromatography analysis, for measuring the phase compositions. The experimental work is complemented with a theoretical modelling for these mixtures, using the statistical association fluid theory for potentials of variable range (SAFT-VR). As an example of the predictive capabilities of the equation, the fluid phase behaviour of the mixture (carbon dioxide + n-decane) is presented. http://dx.doi.org/10.1038/npre.2008.2649.1 Fri, 12 Dec 2008 17:33:17 UTC Measurement & Prediction of Phase Behaviour of Carbon Dioxide Mixtures doi:10.1038/npre.2008.2649.1 2008-12-12 Esther Forte Nature Precedings 2008-12-12T17:33:17Z Poster Chemistry Earth & Environment http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/1720/version/1 This module represents the formalized opinion of the authors and the CARMEN consortium, which identifies the minimum information required to report the use of electrophysiology in a neuroscience study, for submission to the CARMEN system (www.carmen.org.uk). http://precedings.nature.com/documents/1720/version/1 Tue, 25 Mar 2008 18:21:55 UTC Minimum Information about a Neuroscience Investigation (MINI) Electrophysiology hdl:10101/npre.2008.1720.1 2008-03-25 Frank Gibson Nature Precedings 2008-03-25T18:21:55Z Manuscript Neuroscience Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2007.21.1 A cornerstone of systems biology is the use of computational modeling, by which hypotheses can be cast into a quantitative form that can be tested systematically. The use of computational modeling by biologists promises to pave the way for more rigorous analyses of biological functions, and ultimately will lead to new and better treatments for disease.A crucial enabler for more widespread use of computational modeling in biology is reaching agreement on how to represent, store, and communicate models between software tools. The Systems Biology Markup Language (SBML) project is an effort to create a machine-readable format for representing computational models in biology. By supporting SBML as an input and output format, different software tools can operate on the same representation of a model, removing chances for errors in translation and assuring a common starting point for analyses and simulations. SBML has become the most successful effort in this direction so far, with over 100 software systems supporting it today.In this presentation, I will discuss the current state of SBML, including recent developments such as this year’s finalization of Version 2 of SBML Level 2. I will also survey some of the software tools that support SBML, and related projects that have arisen to support more effective use of computational models. Lastly, I will discuss expected future developments in SBML. http://dx.doi.org/10.1038/npre.2007.21.1 Mon, 22 Jan 2007 01:52:11 UTC The Systems Biology Markup Language (SBML): Where It’s Been and Where It’s Going doi:10.1038/npre.2007.21.1 2007-01-22 Michael Hucka Nature Precedings 2007-01-22T01:52:11Z Presentation Biotechnology Bioinformatics http://creativecommons.org/licenses/by/2.5/ http://dx.doi.org/10.1038/npre.2007.20.1 Systems biology has arisen through the convergence of theoretical, computational, and mathematical modeling of systems and the need to understand the wealth of information being rapidly generated in biology. Systems biology by its nature requires collaborations between scientists with expertise in biology, chemistry, computer sciences, engineering, mathematics, and physics. Successful integration of these disciplines depends on bringing to bear both social and technological tools: namely, consortia that help forge collaborations and common understanding, software tools that permit analysis of vast and complex data, and agreed-upon standards that enable researchers to communicate and reuse each other’s results in practical and unambiguous ways. In this presentation, I will discuss several international projects (SBML, SBGN, and BioModels.net) aimed at addressing the last issue.An important prerequisite for effective sharing of computational models is reaching agreement on how to communicate them, both between software and between humans. The Systems Biology Markup Language (SBML) project is an effort to create a machine-readable format for representing computational models at the biochemical reaction level. By supporting SBML as an input and output format, different software tools can operate on the same representation of a model, removing chance for errors in translation and assuring a common starting point for analyses and simulations. SBML has become the most successful effort in this direction so far, with nearly 100 software tools supporting it today.A recently-created sister project is the Systems Biology Graphical Notation (SBGN) project. It addresses the issue of consistent human communication, by attempting to add more rigor and consistency to the graphical network diagrams that often accompany published research on models of biological reaction systems. The real payoff will come when more people and software adopt such a common visual notation and it becomes as familiar to them as circuit schematics are to electronics engineers.Finally, when developing and publishing computational models, it is only natural to want to put them into a database. The BioModels.net project is an effort to (1) provide a free, centralized, publicly-accessible database of human-curated computational models in SBML and other structured formats; (2) define agreed-upon standards for model curation; and (2) define agreed-upon vocabularies for annotating models with connections to biological data resources. http://dx.doi.org/10.1038/npre.2007.20.1 Mon, 22 Jan 2007 01:50:17 UTC Evolving standards and infrastructure for systems biology: SBML, SBGN, and BioModels.net doi:10.1038/npre.2007.20.1 2007-01-22 Michael Hucka Nature Precedings 2007-01-22T01:50:17Z Presentation Biotechnology Bioinformatics http://creativecommons.org/licenses/by/2.5/ http://dx.doi.org/10.1038/npre.2007.19.1 The Systems Biology Markup Language (SBML) is a machine-readable model representation language for software tools in computational systems biology. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. SBML is by no means a perfect format, but it has achieved widespread acceptance as a de facto standard. It is supported worldwide by over 100 software systems (both open-source and commercial). The broad acceptance of a common, open format for exchanging models between software tools is a crucial step towards wider use of quantitative modeling in biology, because it allows researchers to build upon each other’s work with greater ease and accuracy.SBML can encode models consisting of biochemical entities (species) linked by reactions to form networks. An important principle is that models are decomposed into explicitly-labeled constituent elements, the set of which resembles a verbose rendition of chemical reaction equations. The representation deliberately does not cast the model directly into a set of differential equations or other specific interpretation of the model. The formalisms in SBML allows a wide range of biological phenomena to be modeled, including metabolism, cell signaling, gene regulation, and more. Significant flexibility and power comes from the ability to define arbitrary formulae for the rates of change of variables as well as the ability to express other constraints mathematically.This tutorial covered the latest edition of SBML, which is Level 2 Version 2, finalized in September 2006. Topics covered include the basic common principles in SBML as well the changes introduced in Level 2 Version 2. We also discussed software tools for programmers, in particular libSBML. http://dx.doi.org/10.1038/npre.2007.19.1 Mon, 22 Jan 2007 01:48:17 UTC The Systems Biology Markup Language (SBML) Level 2 Version 2 doi:10.1038/npre.2007.19.1 2007-01-22 Michael Hucka Nature Precedings 2007-01-22T01:48:17Z Presentation Biotechnology Bioinformatics http://creativecommons.org/licenses/by/2.5/ http://dx.doi.org/10.1038/npre.2007.18.1 Much academic information can be represented in a structured way and published on the web as XML documents. Such information can then be displayed in a wide variety of ways, using different XSLT stylesheets. This presentation presents MultiGuise, a Web application which allows any of several XML documents to be displayed using any of several stylesheets. Both the documents and the stylesheets are bookmarked in Connotea, from where MultiGuise retrieves them using a special tag. This approach means that anyone can add documents and stylesheets, simply by bookmarking them in Connotea.The approach is illustrated primarily with environmental models represented in XML, but also with examples from SBML (Systems Biology Markup Language) and philosophical arguments marked up in XML. http://dx.doi.org/10.1038/npre.2007.18.1 Sat, 20 Jan 2007 16:47:42 UTC Environmental modelling and Web 2.0 – using Connotea to share XML-represented information doi:10.1038/npre.2007.18.1 2007-01-20 Robert Muetzelfeldt Nature Precedings 2007-01-20T16:47:42Z Presentation Ecology Bioinformatics Earth & Environment http://creativecommons.org/licenses/by/2.5/ http://dx.doi.org/10.1038/npre.2007.17.1 Most simulation models in ecological and environmental research are implemented as computer programs in a conventional programming language. This brief paper argues for a radically different approach, based on the representation of the model structure, relationships and equations in a declarative format (e.g. XML). Simulation code can then be generated from this, but in addition the model can be displayed and processed in a wide range of useful ways, greatly increasing the efficiency and effectiveness of the modelling process. http://dx.doi.org/10.1038/npre.2007.17.1 Sat, 20 Jan 2007 16:41:38 UTC Declarative modelling in the ecological and environmental sciences doi:10.1038/npre.2007.17.1 2007-01-20 Robert Muetzelfeldt Nature Precedings 2007-01-20T16:41:38Z Manuscript Ecology Earth & Environment http://creativecommons.org/licenses/by/2.5/ http://dx.doi.org/10.1038/npre.2006.10.1 The practise of Systems Biology relies on interfaces. Interfacesbetween the entities we study: the paradigm moved from a physicalobject centric view toward a relationship-centric one; interfacesbetween tools: From the retrieval of the primary data to the fineanalysis of a model’s behaviour, one uses many tools, more or lesswell connected; interfaces between individuals: To build anynon-trivial mechanistic model requires to merge existing work andgather external expertise.If we want these interfaces to be generic enough to allow for anybodyto leverage on existing toolkits, a fundamental requirement is theexistence of community-developed well supported standards, but alsoopen resources where to find the “lego” blocks. Over the lasthalf-decade, several efforts have been launched in that direction,whether concerning encoding format, ontologies or databases. Some ofthem are now well-established in the field and play a significant roleto improve its coherence but also to increase the size and the qualityof quantitative models. http://dx.doi.org/10.1038/npre.2006.10.1 Thu, 30 Nov 2006 15:13:38 UTC Open Standards and Resources in Systems Biology: collaborative scale-up toward virtual life doi:10.1038/npre.2006.10.1 2006-11-30 Nicolas Le Novere Nature Precedings 2006-11-30T15:13:38Z Presentation Biotechnology http://creativecommons.org/licenses/by/2.5/ http://dx.doi.org/10.1038/npre.2006.9.1 Integration of neurotransmitter and neuromodulator signals in the striatum plays a central role in the functions and dysfunctions of the basal ganglia. DARPP-32 is a key actor of this integration in the GABAergic medium-size spiny neurons, in particular in response to dopamine and glutamate. When phosphorylated by cAMP-dependent protein kinase (PKA) DARPP-32 inhibits protein phosphatase-1 (PP1), whereas when phosphorylated by cyclin-dependent kinase 5 (CDK5) it inhibits PKA. DARPP-32 is also regulated by casein kinases and by several protein phosphatases. These complex and intricate regulations make simple predictions of DARPP-32 dynamic behaviour virtually impossible. We used detailed quantitative modelling of the regulation of DARPP-32 phosphorylation to improve our understanding of its function. The models included all the combinations of the three best characterized phosphorylation sites of DARPP-32, their regulation by kinases and phosphatases, and the regulation of those enzymes by cAMP and Ca2+ signals. Dynamic simulations allowed to observe the temporal relationships between cAMP and Ca2+ signals. We confirmed that the proposed regulation of protein phosphatase-2A (PP2A) by calcium can account for the observed decrease of Threonine 75 phosphorylation upon glutamate receptor activation. Sensitivity analysis showed that CDK5 activity is a major regulator of the response, as previously suggested. Conversely, the regulation of PP2A by PKA or by calcium, had little effect on the function of DARPP-32 in these conditions. The simulations showed that DARPP-32 is not only a robust signal integrator, but also a coincidence detector, the delay between cAMP and calcium signals affecting the response to the latter. This integration did not depend on the concentration of DARPP-32, while the absolute response on PP1 varied linearly. In silico mutants showed that Ser137 phosphorylation affects the coincidence detector function, and that constitutive phosphorylation in Ser137 transforms DARPP-32 in a quasi-irreversible switch. This work is a first attempt to better understand the complex interactions between cAMP and Ca2+ regulation of DARPP-32. Progressive inclusion of additional components should lead to a realistic model of signalling networks underlying the function of striatal neurons. http://dx.doi.org/10.1038/npre.2006.9.1 Thu, 30 Nov 2006 15:06:03 UTC DARPP-32 is a robust integrator of dopamine and glutamate signals doi:10.1038/npre.2006.9.1 2006-11-30 Nicolas Le Novere Nature Precedings 2006-11-30T15:06:03Z Poster Neuroscience http://creativecommons.org/licenses/by/2.5/