146 results on '"Keating, Sarah M"'
Search Results
2. SBML Level 3: an extensible format for the exchange and reuse of biological models.
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Keating, Sarah M, Waltemath, Dagmar, König, Matthias, Zhang, Fengkai, Dräger, Andreas, Chaouiya, Claudine, Bergmann, Frank T, Finney, Andrew, Gillespie, Colin S, Helikar, Tomáš, Hoops, Stefan, Malik-Sheriff, Rahuman S, Moodie, Stuart L, Moraru, Ion I, Myers, Chris J, Naldi, Aurélien, Olivier, Brett G, Sahle, Sven, Schaff, James C, Smith, Lucian P, Swat, Maciej J, Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J, Blinov, Michael L, Begley, Kimberly, Faeder, James R, Gómez, Harold F, Hamm, Thomas M, Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L, Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J, Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A, Shapiro, Bruce E, Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M, Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C, Hucka, Michael, and SBML Level 3 Community members
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SBML Level 3 Community members ,Animals ,Humans ,Logistic Models ,Systems Biology ,Models ,Biological ,Software ,computational modeling ,file format ,interoperability ,reproducibility ,systems biology ,Bioengineering ,Networking and Information Technology R&D ,Bioinformatics ,Biochemistry and Cell Biology ,Other Biological Sciences - Abstract
Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.
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- 2020
3. Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0
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Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N, Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S, Wachowiak, Jacek, Keating, Sarah M, Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu HJ, Aurich, Maike K, Clancy, Catherine M, Modamio, Jennifer, Sauls, John T, Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C, Valcarcel, Luis V, Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M, Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T, Oliveira, Miguel AP, Vuong, Phan T, El Assal, Lemmer P, Kuperstein, Inna, Zinovyev, Andrei, Hinton, H Scott, Bryant, William A, Aragón Artacho, Francisco J, Planes, Francisco J, Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A, Maranas, Costas D, Lewis, Nathan E, Sauter, Thomas, Palsson, Bernhard Ø, Thiele, Ines, and Fleming, Ronan MT
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Information and Computing Sciences ,Biochemistry and Cell Biology ,Biological Sciences ,Biotechnology ,Genome ,Metabolic Networks and Pathways ,Models ,Biological ,Software ,Systems Biology ,q-bio.QM ,Chemical Sciences ,Medical and Health Sciences ,Bioinformatics - Abstract
Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.
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- 2019
4. Specifications of standards in systems and synthetic biology: status and developments in 2022 and the COMBINE meeting 2022
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König Matthias, Gleeson Padraig, Golebiewski Martin, Gorochowski Thomas E., Hucka Michael, Keating Sarah M., Myers Chris J., Nickerson David P., Sommer Björn, Waltemath Dagmar, and Schreiber Falk
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Biotechnology ,TP248.13-248.65 - Abstract
This special issue of the Journal of Integrative Bioinformatics contains updated specifications of COMBINE standards in systems and synthetic biology. The 2022 special issue presents three updates to the standards: CellML 2.0.1, SBML Level 3 Package: Spatial Processes, Version 1, Release 1, and Synthetic Biology Open Language (SBOL) Version 3.1.0. This document can also be used to identify the latest specifications for all COMBINE standards. In addition, this editorial provides a brief overview of the COMBINE 2022 meeting in Berlin.
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- 2023
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5. Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0
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Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N., Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu H. J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, Assal, Diana C. El, Valcarcel, Luis V., Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Guebila, Marouen Ben, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A. P., Vuong, Phan T., Assal, Lemmer P. El, Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Artacho, Francisco J. Aragón, Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard Ø., Thiele, Ines, and Fleming, Ronan M. T.
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Quantitative Biology - Quantitative Methods - Abstract
COnstraint-Based Reconstruction and Analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive software suite of interoperable COBRA methods. It has found widespread applications in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. Version 3.0 includes new methods for quality controlled reconstruction, modelling, topological analysis, strain and experimental design, network visualisation as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimisation solvers for multi-scale, multi-cellular and reaction kinetic modelling, respectively. This protocol can be adapted for the generation and analysis of a constraint-based model in a wide variety of molecular systems biology scenarios. This protocol is an update to the COBRA Toolbox 1.0 and 2.0. The COBRA Toolbox 3.0 provides an unparalleled depth of constraint-based reconstruction and analysis methods.
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- 2017
6. Specifications of standards in systems and synthetic biology: status and developments in 2021
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Schreiber Falk, Gleeson Padraig, Golebiewski Martin, Gorochowski Thomas E., Hucka Michael, Keating Sarah M., König Matthias, Myers Chris J., Nickerson David P., Sommer Björn, and Waltemath Dagmar
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Biotechnology ,TP248.13-248.65 - Abstract
This special issue of the Journal of Integrative Bioinformatics contains updated specifications of COMBINE standards in systems and synthetic biology. The 2021 special issue presents four updates of standards: Synthetic Biology Open Language Visual Version 2.3, Synthetic Biology Open Language Visual Version 3.0, Simulation Experiment Description Markup Language Level 1 Version 4, and OMEX Metadata specification Version 1.2. This document can also be consulted to identify the latest specifications of all COMBINE standards.
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- 2021
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7. The first 10 years of the international coordination network for standards in systems and synthetic biology (COMBINE)
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Waltemath Dagmar, Golebiewski Martin, Blinov Michael L, Gleeson Padraig, Hermjakob Henning, Hucka Michael, Inau Esther Thea, Keating Sarah M, König Matthias, Krebs Olga, Malik-Sheriff Rahuman S, Nickerson David, Oberortner Ernst, Sauro Herbert M, Schreiber Falk, Smith Lucian, Stefan Melanie I, Wittig Ulrike, and Myers Chris J
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combine ,community building ,meeting report ,standardization ,Biotechnology ,TP248.13-248.65 - Abstract
This paper presents a report on outcomes of the 10th Computational Modeling in Biology Network (COMBINE) meeting that was held in Heidelberg, Germany, in July of 2019. The annual event brings together researchers, biocurators and software engineers to present recent results and discuss future work in the area of standards for systems and synthetic biology. The COMBINE initiative coordinates the development of various community standards and formats for computational models in the life sciences. Over the past 10 years, COMBINE has brought together standard communities that have further developed and harmonized their standards for better interoperability of models and data. COMBINE 2019 was co-located with a stakeholder workshop of the European EU-STANDS4PM initiative that aims at harmonized data and model standardization for in silico models in the field of personalized medicine, as well as with the FAIRDOM PALs meeting to discuss findable, accessible, interoperable and reusable (FAIR) data sharing. This report briefly describes the work discussed in invited and contributed talks as well as during breakout sessions. It also highlights recent advancements in data, model, and annotation standardization efforts. Finally, this report concludes with some challenges and opportunities that this community will face during the next 10 years.
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- 2020
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8. Specifications of standards in systems and synthetic biology: status and developments in 2020
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Schreiber Falk, Sommer Björn, Czauderna Tobias, Golebiewski Martin, Gorochowski Thomas E., Hucka Michael, Keating Sarah M., König Matthias, Myers Chris, Nickerson David, and Waltemath Dagmar
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ontologies ,standards ,systems biology ,synthetic biology ,Biotechnology ,TP248.13-248.65 - Abstract
This special issue of the Journal of Integrative Bioinformatics presents papers related to the 10th COMBINE meeting together with the annual update of COMBINE standards in systems and synthetic biology.
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- 2020
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9. SBML Qualitative Models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools
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Chaouiya, Claudine, Berenguier, Duncan, Keating, Sarah M, Naldi, Aurelien, van Iersel, Martijn P., Rodriguez, Nicolas, Dräger, Andreas, Büchel, Finja, Cokelaer, Thomas, Kowal, Bryan, Wicks, Benjamin, Gonçalves, Emanuel, Dorier, Julien, Page, Michel, Monteiro, Pedro T., von Kamp, Axel, Xenarios, Ioannis, de Jong, Hidde, Hucka, Michael, Klamt, Steffen, Thieffry, Denis, Novère, Nicolas Le, Saez-Rodriguez, Julio, and Helikar, Tomáš
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Quantitative Biology - Molecular Networks - Abstract
Background: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. Results: We present the System Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the cooperative development of the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyze qualitative models. Conclusion: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks., Comment: 29 pages, 7 figures
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- 2013
10. Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2019
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Schreiber Falk, Sommer Björn, Bader Gary D., Gleeson Padraig, Golebiewski Martin, Hucka Michael, Keating Sarah M., König Matthias, Myers Chris, Nickerson David, and Waltemath Dagmar
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Biotechnology ,TP248.13-248.65 - Abstract
This special issue of the Journal of Integrative Bioinformatics presents an overview of COMBINE standards and their latest specifications. The standards cover representation formats for computational modeling in synthetic and systems biology and include BioPAX, CellML, NeuroML, SBML, SBGN, SBOL and SED-ML. The articles in this issue contain updated specifications of SBGN Process Description Level 1 Version 2, SBML Level 3 Core Version 2 Release 2, SBOL Version 2.3.0, and SBOL Visual Version 2.1.
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- 2019
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11. Systems biology markup language (SBML) level 3 package: multistate, multicomponent and multicompartment species, version 1, release 2
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Zhang Fengkai, Smith Lucian P., Blinov Michael L., Faeder James, Hlavacek William S., Juan Tapia Jose, Keating Sarah M., Rodriguez Nicolas, Dräger Andreas, Harris Leonard A., Finney Andrew, Hu Bin, Hucka Michael, and Meier-Schellersheim Martin
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rule-based modeling ,specification ,standard ,systems biology ,Biotechnology ,TP248.13-248.65 - Abstract
Rule-based modeling is an approach that permits constructing reaction networks based on the specification of rules for molecular interactions and transformations. These rules can encompass details such as the interacting sub-molecular domains and the states and binding status of the involved components. Conceptually, fine-grained spatial information such as locations can also be provided. Through “wildcards” representing component states, entire families of molecule complexes sharing certain properties can be specified as patterns. This can significantly simplify the definition of models involving species with multiple components, multiple states, and multiple compartments. The systems biology markup language (SBML) Level 3 Multi Package Version 1 extends the SBML Level 3 Version 1 core with the “type” concept in the Species and Compartment classes. Therefore, reaction rules may contain species that can be patterns and exist in multiple locations. Multiple software tools such as Simmune and BioNetGen support this standard that thus also becomes a medium for exchanging rule-based models. This document provides the specification for Release 2 of Version 1 of the SBML Level 3 Multi package. No design changes have been made to the description of models between Release 1 and Release 2; changes are restricted to the correction of errata and the addition of clarifications.
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- 2020
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12. Systems Biology Markup Language (SBML) Level 3 Package: Distributions, Version 1, Release 1
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Smith Lucian P., Moodie Stuart L., Bergmann Frank T., Gillespie Colin, Keating Sarah M., König Matthias, Myers Chris J., Swat Maciek J., Wilkinson Darren J., and Hucka Michael
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distributions ,modeling ,sbml ,systems biology ,uncertainty ,Biotechnology ,TP248.13-248.65 - Abstract
Biological models often contain elements that have inexact numerical values, since they are based on values that are stochastic in nature or data that contains uncertainty. The Systems Biology Markup Language (SBML) Level 3 Core specification does not include an explicit mechanism to include inexact or stochastic values in a model, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactic constructs. The SBML Distributions package for SBML Level 3 adds the necessary features to allow models to encode information about the distribution and uncertainty of values underlying a quantity.
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- 2020
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13. Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2017
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Schreiber Falk, Bader Gary D., Gleeson Padraig, Golebiewski Martin, Hucka Michael, Keating Sarah M., Novère Nicolas Le, Myers Chris, Nickerson David, Sommer Björn, and Waltemath Dagmar
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combine ,systems biology ,synthetic biology ,standards ,Biotechnology ,TP248.13-248.65 - Abstract
Standards are essential to the advancement of Systems and Synthetic Biology. COMBINE provides a formal body and a centralised platform to help develop and disseminate relevant standards and related resources. The regular special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards by providing unified, easily citable access. This paper provides an overview of existing COMBINE standards and presents developments of the last year.
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- 2018
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14. The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 2 Core Release 2
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Hucka Michael, Bergmann Frank T., Chaouiya Claudine, Dräger Andreas, Hoops Stefan, Keating Sarah M., König Matthias, Novère Nicolas Le, Myers Chris J., Olivier Brett G., Sahle Sven, Schaff James C., Sheriff Rahuman, Smith Lucian P., Waltemath Dagmar, Wilkinson Darren J., and Zhang Fengkai
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systems biology markup language ,standards ,visualization ,representation ,Biotechnology ,TP248.13-248.65 - Abstract
Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. 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. This document provides the specification for Release 2 of Version 2 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. Release 2 corrects some errors and clarifies some ambiguities discovered in Release 1. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project website at http://sbml.org/.
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- 2019
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15. The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core
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Hucka Michael, Bergmann Frank T., Dräger Andreas, Hoops Stefan, Keating Sarah M., Le Novère Nicolas, Myers Chris J., Olivier Brett G., Sahle Sven, Schaff James C., Smith Lucian P., Waltemath Dagmar, and Wilkinson Darren J.
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sbml ,modeling ,standards ,Biotechnology ,TP248.13-248.65 - Abstract
Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. 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. This document provides the specification for Release 2 of Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML, their encoding in XML (the eXtensible Markup Language), validation rules that determine the validity of an SBML document, and examples of models in SBML form. No design changes have been made to the description of models between Release 1 and Release 2; changes are restricted to the format of annotations, the correction of errata and the addition of clarifications. Other materials and software are available from the SBML project website at http://sbml.org/.
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- 2018
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16. SBML Level 3 package: Render, Version 1, Release 1
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Bergmann Frank T., Keating Sarah M., Gauges Ralph, Sahle Sven, and Wengler Katja
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sbml ,render ,visualisation ,Biotechnology ,TP248.13-248.65 - Abstract
Many software tools provide facilities for depicting reaction network diagrams in a visual form. Two aspects of such a visual diagram can be distinguished: the layout (i.e.: the positioning and connections) of the elements in the diagram, and the graphical form of the elements (for example, the glyphs used for symbols, the properties of the lines connecting them, and so on). This document describes the SBML Level 3 Render package that complements the SBML Level 3 Layout package and provides a means of capturing the precise rendering of the elements in a diagram. The SBML Level 3 Render package provides a flexible approach to rendering that is independent of both the underlying SBML model and the Layout information. There can be one block of render information that applies to all layouts or an additional block for each layout. Many of the elements used in the current render specification are based on corresponding elements from the SVG specification. This allows us to easily convert a combination of layout information and render information into a SVG drawing.
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- 2018
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17. The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 2 Core
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Hucka Michael, Bergmann Frank T., Dräger Andreas, Hoops Stefan, Keating Sarah M., Le Novère Nicolas, Myers Chris J., Olivier Brett G., Sahle Sven, Schaff James C., Smith Lucian P., Waltemath Dagmar, and Wilkinson Darren J.
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sbml ,modeling ,computational biology ,systems biology ,standards ,Biotechnology ,TP248.13-248.65 - Abstract
Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. 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. This document provides the specification for Version 2 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML, their encoding in XML (the eXtensible Markup Language), validation rules that determine the validity of an SBML document, and examples of models in SBML form. The design of Version 2 differs from Version 1 principally in allowing new MathML constructs, making more child elements optional, and adding identifiers to all SBML elements instead of only selected elements. Other materials and software are available from the SBML project website at http://sbml.org/.
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- 2018
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18. Encoding Neuronal Models in SBML
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Keating, Sarah M., Le Novère, Nicolas, and Le Novère, N., editor
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- 2012
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19. Systems Biology Markup Language (SBML) Level 2 Version 5: Structures and Facilities for Model Definitions
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Hucka Michael, Bergmann Frank T., Dräger Andreas, Hoops Stefan, Keating Sarah M., Le Novère Nicolas, Myers Chris J., Olivier Brett G., Sahle Sven, Schaff James C., Smith Lucian P., Waltemath Dagmar, and Wilkinson Darren J.
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Biotechnology ,TP248.13-248.65 - Abstract
Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. 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. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.
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- 2015
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20. SBML Level 3 package: Qualitative Models, Version 1, Release 1
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Chaouiya Claudine, Keating Sarah M., Berenguier Duncan, Naldi Aurélien, Thieffry Denis, Iersel Martijn P. van, Le Novère Nicolas, and Helikar Tomáš
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Biotechnology ,TP248.13-248.65 - Abstract
Quantitative methods for modelling biological networks require an in-depth knowledge of the biochemical reactions and their stoichiometric and kinetic parameters. In many practical cases, this knowledge is missing. This has led to the development of several qualitative modelling methods using information such as, for example, gene expression data coming from functional genomic experiments. The SBML Level 3 Version 1 Core specification does not provide a mechanism for explicitly encoding qualitative models, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactical constructs.
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- 2015
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21. The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core
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Hucka Michael, Bergmann Frank T., Hoops Stefan, Keating Sarah M., Sahle Sven, Schaff James C., Smith Lucian P., and Wilkinson Darren J.
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Biotechnology ,TP248.13-248.65 - Abstract
Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. 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. This document provides the specification for Version 1 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.
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- 2015
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22. SBML Models and MathSBML
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Shapiro, Bruce E., Finney, Andrew, Hucka, Michael, Bornstein, Benjamin, Funahashi, Akira, Jouraku, Akiya, Keating, Sarah M., Le Novère, Nicolas, Matthews, Joanne, Schilstra, Maria J., and Choi, Sangdun, editor
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- 2007
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23. cellmlmanip and chaste_codegen: automatic CellML to C++ code generation with fixes for singularities and automatically generated Jacobians
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Hendrix, Maurice, primary, Clerx, Michael, additional, Tamuri, Asif U, additional, Keating, Sarah M, additional, Johnstone, Ross H, additional, Cooper, Jonathan, additional, and Mirams, Gary R, additional
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- 2022
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24. Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology
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Niarakis, Anna, primary, Waltemath, Dagmar, additional, Glazier, James, additional, Schreiber, Falk, additional, Keating, Sarah M, additional, Nickerson, David, additional, Chaouiya, Claudine, additional, Siegel, Anne, additional, Noël, Vincent, additional, Hermjakob, Henning, additional, Helikar, Tomáš, additional, Soliman, Sylvain, additional, and Calzone, Laurence, additional
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- 2022
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25. chaste codegen: automatic CellML to C++ code generation with fixes for singularities and automatically generated Jacobians
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Hendrix, Maurice, Clerx, Michael, Tamuri, Asif U, Keating, Sarah M, Johnstone, Ross H, Cooper, Jonathan, and Mirams, Gary R
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IRC - Data Modelling & Uncertainty ,Centre for Mathematical Medicine and Biology ,Global Research Theme - Health and Wellbeing ,Computing & Mathematics - Applied Mathematics ,Medicine (miscellaneous) ,General Biochemistry, Genetics and Molecular Biology - Abstract
Hundreds of different mathematical models have been proposed for describing electrophysiology of various cell types. These models are quite complex (nonlinear systems of typically tens of ODEs and sometimes hundreds of parameters) and software packages such as the Cancer, Heart and Soft Tissue Environment (Chaste) C++ library have been designed to run simulations with these models in isolation or coupled to form a tissue simulation. The complexity of many of these models makes sharing and translating them to new simulation environments difficult. CellML is an XML format that offers a solution to this problem and has been widely-adopted. This paper specifically describes the capabilities of chaste_codegen, a Python-based CellML to C++ converter based on the new cellmlmanip Python library for reading and manipulating CellML models. While chaste_codegen is a Python 3 redevelopment of a previous Python 2 tool (called PyCML) it has some additional new features that this paper describes. Most notably, chaste_codegen has the ability to generate analytic Jacobians without the use of proprietary software, and also to find singularities occurring in equations and automatically generate and apply linear approximations to prevent numerical problems at these points.
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- 2022
26. chaste codegen: automatic CellML to C++ code generation with fixes for singularities and automatically generated Jacobians
- Author
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Hendrix, Maurice, primary, Clerx, Michael, additional, Tamuri, Asif U, additional, Keating, Sarah M, additional, Johnstone, Ross H, additional, Cooper, Jonathan, additional, and Mirams, Gary R, additional
- Published
- 2021
- Full Text
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27. Wikidata as a knowledge graph for the life sciences
- Author
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Waagmeester, Andra, Stupp, Gregory, Burgstaller-Muehlbacher, Sebastian, Good, Benjamin M, Griffith, Malachi, Obi L Griffith, Hanspers, Kristina, Hermjakob, Henning, Hudson, Toby S, Hybiske, Kevin, Keating, Sarah M, Manske, Magnus, Mayers, Michael, Mietchen, Daniel, Mitraka, Elvira, Pico, Alexander R, Putman, Timothy, Riutta, Anders, Queralt-Rosinach, Nuria, Schriml, Lynn M, Shafee, Thomas, Slenter, Denise, Stephan, Ralf, Thornton, Katherine, Tsueng, Ginger, Tu, Roger, Ul-Hasan, Sabah, Willighagen, Egon, and Chunlei Wu
- Subjects
ComputingMethodologies_PATTERNRECOGNITION ,Uncategorized - Abstract
© Waagmeester et al. Wikidata is a community-maintained knowledge base that has been assembled from repositories in the fields of genomics, proteomics, genetic variants, pathways, chemical compounds, and diseases, and that adheres to the FAIR principles of findability, accessibility, interoperability and reusability. Here we describe the breadth and depth of the biomedical knowledge contained within Wikidata, and discuss the open-source tools we have built to add information to Wikidata and to synchronize it with source databases. We also demonstrate several use cases for Wikidata, including the crowdsourced curation of biomedical ontologies, phenotype-based diagnosis of disease, and drug repurposing.
- Published
- 2021
- Full Text
- View/download PDF
28. Computational Biology Library Framework
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Keating, Sarah M
- Subjects
COMBINE - Abstract
Presentation on the Computational Biology Library Framework project funded by the CZI and the aims of the grant.
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- 2020
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29. SBML Level 3: an extensible format for the exchange and reuse of biological models
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Keating, Sarah M., Gómez, Harold F., Stelling, Jörg, and SBML Level 3 Community members
- Subjects
Computational modeling ,File format ,Systems biology ,Reproducibility - Abstract
Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction‐based models and packages that extend the core with features suited to other model types including constraint‐based models, reaction‐diffusion models, logical network models, and rule‐based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single‐cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution., Molecular Systems Biology, 16 (8), ISSN:1744-4292
- Published
- 2020
30. SCIENCE FORUM Wikidata as a knowledge graph for the life sciences
- Author
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Waagmeester, Andra, Stupp, Gregory, Burgstaller-muehlbacher, Sebastian, Good, Benjamin M, Griffith, Malachi, Griffith, Obi L, Hanspers, Kristina, Hermjakob, Henning, Hudson, Toby S, Hybiske, Kevin, Keating, Sarah M, Manske, Magnus, Mayers, Michael, Mietchen, Daniel, Mitraka, Elvira, Pico, Alexander R, Putman, Timothy, Riutta, Anders, Queralt-rosinach, Nuria, Schriml, Lynn M, Shafee, Thomas, Slenter, Denise, Stephan, Ralf, Thornton, Katherine, Tsueng, Ginger, Tu, Roger, Ul-hasan, Sabah, Willighagen, Egon, Wu, Chunlei, Su, Andrew I, Bioinformatica, and RS: NUTRIM - R1 - Obesity, diabetes and cardiovascular health
- Subjects
DISORDER ,ComputingMethodologies_PATTERNRECOGNITION - Abstract
Wikidata is a community-maintained knowledge base that has been assembled from repositories in the fields of genomics, proteomics, genetic variants, pathways, chemical compounds, and diseases, and that adheres to the FAIR principles of findability, accessibility, interoperability and reusability. Here we describe the breadth and depth of the biomedical knowledge contained within Wikidata, and discuss the open-source tools we have built to add information to Wikidata and to synchronize it with source databases. We also demonstrate several use cases for Wikidata, including the crowdsourced curation of biomedical ontologies, phenotype-based diagnosis of disease, and drug repurposing.
- Published
- 2020
31. SBML Level 3: an extensible format for the exchange and reuse of biological models
- Author
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Computer Science, Keating, Sarah M., Waltemath, Dagmar, Koenig, Matthias, Zhang, Fengkai, Draeger, Andreas, Chaouiya, Claudine, Bergmann, Frank T., Finney, Andrew, Gillespie, Colin S., Helikar, Tomas, Hoops, Stefan, Malik-Sheriff, Rahuman S., Moodie, Stuart L., Moraru, Ion I., Myers, Chris J., Naldi, Aurelien, Olivier, Brett G., Sahle, Sven, Schaff, James C., Smith, Lucian P., Swat, Maciej J., Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J., Blinov, Michael L., Begley, Kimberly, Faeder, James R., Gomez, Harold F., Hamm, Thomas M., Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L., Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J., Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A., Shapiro, Bruce E., Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M., Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C., Hucka, Michael, Computer Science, Keating, Sarah M., Waltemath, Dagmar, Koenig, Matthias, Zhang, Fengkai, Draeger, Andreas, Chaouiya, Claudine, Bergmann, Frank T., Finney, Andrew, Gillespie, Colin S., Helikar, Tomas, Hoops, Stefan, Malik-Sheriff, Rahuman S., Moodie, Stuart L., Moraru, Ion I., Myers, Chris J., Naldi, Aurelien, Olivier, Brett G., Sahle, Sven, Schaff, James C., Smith, Lucian P., Swat, Maciej J., Thieffry, Denis, Watanabe, Leandro, Wilkinson, Darren J., Blinov, Michael L., Begley, Kimberly, Faeder, James R., Gomez, Harold F., Hamm, Thomas M., Inagaki, Yuichiro, Liebermeister, Wolfram, Lister, Allyson L., Lucio, Daniel, Mjolsness, Eric, Proctor, Carole J., Raman, Karthik, Rodriguez, Nicolas, Shaffer, Clifford A., Shapiro, Bruce E., Stelling, Joerg, Swainston, Neil, Tanimura, Naoki, Wagner, John, Meier-Schellersheim, Martin, Sauro, Herbert M., Palsson, Bernhard, Bolouri, Hamid, Kitano, Hiroaki, Funahashi, Akira, Hermjakob, Henning, Doyle, John C., and Hucka, Michael
- Abstract
Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developedSBMLLevel 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades ofSBMLand a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and howSBMLLevel 3 provides the foundation needed to support this evolution.
- Published
- 2020
32. Supporting SBML as a Model Exchange Format in Software Applications
- Author
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Keating, Sarah M., primary and Le Novère, Nicolas, additional
- Published
- 2013
- Full Text
- View/download PDF
33. Methods for Simulating the Dynamics of Complex Biological Processes
- Author
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Schilstra, Maria J., primary, Martin, Stephen R., additional, and Keating, Sarah M., additional
- Published
- 2008
- Full Text
- View/download PDF
34. Wikidata as a knowledge graph for the life sciences
- Author
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Waagmeester, Andra, primary, Stupp, Gregory, additional, Burgstaller-Muehlbacher, Sebastian, additional, Good, Benjamin M, additional, Griffith, Malachi, additional, Griffith, Obi L, additional, Hanspers, Kristina, additional, Hermjakob, Henning, additional, Hudson, Toby S, additional, Hybiske, Kevin, additional, Keating, Sarah M, additional, Manske, Magnus, additional, Mayers, Michael, additional, Mietchen, Daniel, additional, Mitraka, Elvira, additional, Pico, Alexander R, additional, Putman, Timothy, additional, Riutta, Anders, additional, Queralt-Rosinach, Nuria, additional, Schriml, Lynn M, additional, Shafee, Thomas, additional, Slenter, Denise, additional, Stephan, Ralf, additional, Thornton, Katherine, additional, Tsueng, Ginger, additional, Tu, Roger, additional, Ul-Hasan, Sabah, additional, Willighagen, Egon, additional, Wu, Chunlei, additional, and Su, Andrew I, additional
- Published
- 2020
- Full Text
- View/download PDF
35. Author response: Wikidata as a knowledge graph for the life sciences
- Author
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Waagmeester, Andra, primary, Stupp, Gregory, additional, Burgstaller-Muehlbacher, Sebastian, additional, Good, Benjamin M, additional, Griffith, Malachi, additional, Griffith, Obi L, additional, Hanspers, Kristina, additional, Hermjakob, Henning, additional, Hudson, Toby S, additional, Hybiske, Kevin, additional, Keating, Sarah M, additional, Manske, Magnus, additional, Mayers, Michael, additional, Mietchen, Daniel, additional, Mitraka, Elvira, additional, Pico, Alexander R, additional, Putman, Timothy, additional, Riutta, Anders, additional, Queralt-Rosinach, Nuria, additional, Schriml, Lynn M, additional, Shafee, Thomas, additional, Slenter, Denise, additional, Stephan, Ralf, additional, Thornton, Katherine, additional, Tsueng, Ginger, additional, Tu, Roger, additional, Ul-Hasan, Sabah, additional, Willighagen, Egon, additional, Wu, Chunlei, additional, and Su, Andrew I, additional
- Published
- 2020
- Full Text
- View/download PDF
36. Software Infrastructure for Effective Communication and Reuse of Computational Models
- Author
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Finney, Andrew, primary, Hucka, Michael, additional, Bornstein, Benjamin J., additional, Keating, Sarah M., additional, Shapiro, Bruce E., additional, Matthews, Joanne, additional, Kovitz, Ben L., additional, Schilstra, Maria J., additional, Funahashi, Akira, additional, Doyle, John, additional, and Kitano, Hiroaki, additional
- Published
- 2006
- Full Text
- View/download PDF
37. LibSBML: an API Library for SBML
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Bornstein, Benjamin J., Keating, Sarah M., Jouraku, Akiya, and Hucka, Michael
- Published
- 2008
38. SBMLToolbox: an SBML toolbox for MATLAB users
- Author
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Keating, Sarah M., Bornstein, Benjamin J., Finney, Andrew, and Hucka, Michael
- Published
- 2006
39. Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0
- Author
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Universidad de Alicante. Departamento de Matemáticas, Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N., Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu H.J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C., Valcarcel, Luis V., Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A.P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragón Artacho, Francisco Javier, Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard Ø., Thiele, Ines, Fleming, Ronan M.T., Universidad de Alicante. Departamento de Matemáticas, Heirendt, Laurent, Arreckx, Sylvain, Pfau, Thomas, Mendoza, Sebastián N., Richelle, Anne, Heinken, Almut, Haraldsdóttir, Hulda S., Wachowiak, Jacek, Keating, Sarah M., Vlasov, Vanja, Magnusdóttir, Stefania, Ng, Chiam Yu, Preciat, German, Žagare, Alise, Chan, Siu H.J., Aurich, Maike K., Clancy, Catherine M., Modamio, Jennifer, Sauls, John T., Noronha, Alberto, Bordbar, Aarash, Cousins, Benjamin, El Assal, Diana C., Valcarcel, Luis V., Apaolaza, Iñigo, Ghaderi, Susan, Ahookhosh, Masoud, Ben Guebila, Marouen, Kostromins, Andrejs, Sompairac, Nicolas, Le, Hoai M., Ma, Ding, Sun, Yuekai, Wang, Lin, Yurkovich, James T., Oliveira, Miguel A.P., Vuong, Phan T., El Assal, Lemmer P., Kuperstein, Inna, Zinovyev, Andrei, Hinton, H. Scott, Bryant, William A., Aragón Artacho, Francisco Javier, Planes, Francisco J., Stalidzans, Egils, Maass, Alejandro, Vempala, Santosh, Hucka, Michael, Saunders, Michael A., Maranas, Costas D., Lewis, Nathan E., Sauter, Thomas, Palsson, Bernhard Ø., Thiele, Ines, and Fleming, Ronan M.T.
- Abstract
Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.
- Published
- 2019
40. BioModels—15 years of sharing computational models in life science
- Author
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Malik-Sheriff, Rahuman S, primary, Glont, Mihai, additional, Nguyen, Tung V N, additional, Tiwari, Krishna, additional, Roberts, Matthew G, additional, Xavier, Ashley, additional, Vu, Manh T, additional, Men, Jinghao, additional, Maire, Matthieu, additional, Kananathan, Sarubini, additional, Fairbanks, Emma L, additional, Meyer, Johannes P, additional, Arankalle, Chinmay, additional, Varusai, Thawfeek M, additional, Knight-Schrijver, Vincent, additional, Li, Lu, additional, Dueñas-Roca, Corina, additional, Dass, Gaurhari, additional, Keating, Sarah M, additional, Park, Young M, additional, Buso, Nicola, additional, Rodriguez, Nicolas, additional, Hucka, Michael, additional, and Hermjakob, Henning, additional
- Published
- 2019
- Full Text
- View/download PDF
41. Wikidata as a FAIR knowledge graph for the life sciences
- Author
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Waagmeester, Andra, primary, Stupp, Gregory, additional, Burgstaller-Muehlbacher, Sebastian, additional, Good, Benjamin M., additional, Griffith, Malachi, additional, Griffith, Obi, additional, Hanspers, Kristina, additional, Hermjakob, Henning, additional, Hudson, Toby S., additional, Hybiske, Kevin, additional, Keating, Sarah M., additional, Manske, Magnus, additional, Mayers, Michael, additional, Mietchen, Daniel, additional, Mitraka, Elvira, additional, Pico, Alexander R., additional, Putman, Timothy, additional, Riutta, Anders, additional, Queralt-Rosinach, Núria, additional, Schriml, Lynn M., additional, Shafee, Thomas, additional, Slenter, Denise, additional, Stephan, Ralf, additional, Thornton, Katherine, additional, Tsueng, Ginger, additional, Tu, Roger, additional, Ul-Hasan, Sabah, additional, Willighagen, Egon, additional, Wu, Chunlei, additional, and Su, Andrew I., additional
- Published
- 2019
- Full Text
- View/download PDF
42. BioModels—15 years of sharing computational models in life science.
- Author
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Malik-Sheriff, Rahuman S, Glont, Mihai, Nguyen, Tung V N, Tiwari, Krishna, Roberts, Matthew G, Xavier, Ashley, Vu, Manh T, Men, Jinghao, Maire, Matthieu, Kananathan, Sarubini, Fairbanks, Emma L, Meyer, Johannes P, Arankalle, Chinmay, Varusai, Thawfeek M, Knight-Schrijver, Vincent, Li, Lu, Dueñas-Roca, Corina, Dass, Gaurhari, Keating, Sarah M, and Park, Young M
- Published
- 2020
- Full Text
- View/download PDF
43. MOCCASIN: converting MATLAB ODE models to SBML
- Author
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Gómez, Harold F., primary, Hucka, Michael, additional, Keating, Sarah M., additional, Nudelman, German, additional, Iber, Dagmar, additional, and Sealfon, Stuart C., additional
- Published
- 2016
- Full Text
- View/download PDF
44. A profile of today's SBML-compatible software
- Author
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Hucka, Michael, Bergmann, Frank T., Keating, Sarah M., Smith, Lucian P., Hucka, Michael, Bergmann, Frank T., Keating, Sarah M., and Smith, Lucian P.
- Abstract
Computational systems biologists today have a healthy selection of software resources to help them do research. Many software packages, especially those concerned with computational modeling, have adopted SBML (the Systems Biology Markup Language) as a machine-readable format to permit users to exchange models. Our group has a keen interest in understanding the landscape of SBML support. To help us ascertain the state of modern SBML-compatible software, in mid-2011 we initiated a survey of software packages that support SBML. Here we report the preliminary survey results. Based on 81 packages for which we have data so far, we summarize the trends in six areas: (1) What are the major types of functionality offered by the software systems? (2) What mathematical frameworks do they support? (3) What are their SBML-specific capabilities? (4) What other standards do they support besides SBML? (5) What are their characteristics with respect to run-time environments? And finally, (6) what are the availability and licensing terms?
- Published
- 2011
45. The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core
- Author
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Hucka, Michael, Bergmann, Frank T., Hoops, Stefan, Keating, Sarah M., Sahle, Sven, Schaff, James C., Smith, Lucian P., Wilkinson, Darren J., Hucka, Michael, Bergmann, Frank T., Hoops, Stefan, Keating, Sarah M., Sahle, Sven, Schaff, James C., Smith, Lucian P., and Wilkinson, Darren J.
- Abstract
This document defines Version 1 of the Systems Biology Markup Language (SBML) Level 3 Core, an electronic model representation format for systems biology. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. SBML is defined neutrally with respect to programming languages and software encoding; however, it is oriented primarily towards allowing models to be encoded using XML, the eXtensible Markup Language (Bray et al., 2004). This document contains many examples of SBML models written in XML. Formal schemas describing the syntax of SBML, as well as other materials and software, are available from the SBML project web site, http://sbml.org/. The SBML project is not an attempt to define a universal language for representing quantitative models. The rapidly evolving views of biological function, coupled with the vigorous rates at which new computational techniques and individual tools are being developed today, are incompatible with a one-size-fits-all idea of a universal language. A more realistic alternative is to acknowledge the diversity of approaches and methods being explored by different software tool developers, and seek a common intermediate format—a lingua franca—enabling communication of the most essential aspects of the models. The definition of the model description language presented here does not specify how programs should communicate or read/write SBML. We assume that for a simulation program to communicate a model encoded in SBML, the program will have to translate its internal data structures to and from SBML, use a suitable transmission medium and protocol, etc., but these issues are outside the scope of this document.
- Published
- 2010
46. SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools
- Author
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Chaouiya, Claudine, primary, Bérenguier, Duncan, additional, Keating, Sarah M, additional, Naldi, Aurélien, additional, van Iersel, Martijn P, additional, Rodriguez, Nicolas, additional, Dräger, Andreas, additional, Büchel, Finja, additional, Cokelaer, Thomas, additional, Kowal, Bryan, additional, Wicks, Benjamin, additional, Gonçalves, Emanuel, additional, Dorier, Julien, additional, Page, Michel, additional, Monteiro, Pedro T, additional, von Kamp, Axel, additional, Xenarios, Ioannis, additional, de Jong, Hidde, additional, Hucka, Michael, additional, Klamt, Steffen, additional, Thieffry, Denis, additional, Le Novère, Nicolas, additional, Saez-Rodriguez, Julio, additional, and Helikar, Tomáš, additional
- Published
- 2013
- Full Text
- View/download PDF
47. SBML Models and MathSBML
- Author
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Choi, Sangdun, Shapiro, Bruce E., Finney, Andrew, Hucka, Michael, Bornstein, Benjamin, Funahashi, Akira, Jouraku, Akiya, Keating, Sarah M., Le Novère, Nicolas, Matthews, Joanne, Schilstra, Maria J., Choi, Sangdun, Shapiro, Bruce E., Finney, Andrew, Hucka, Michael, Bornstein, Benjamin, Funahashi, Akira, Jouraku, Akiya, Keating, Sarah M., Le Novère, Nicolas, Matthews, Joanne, and Schilstra, Maria J.
- Abstract
MathSBML is an open-source, freely-downloadable Mathematica package that facilitates working with Systems Biology Markup Language (SBML) models. SBML is a tool-neutral, computer-readable format for representing models of biochemical reaction networks, applicable to metabolic networks, cell-signaling pathways, genomic regulatory networks, and other modeling problems in systems biology that is widely supported by the systems biology community. SBML is based on XML, a standard medium for representing and transporting data that is widely supported on the internet as well as in computational biology and bioinformatics. Because SBML is tool-independent, it enables model transportability, reuse, publication and survival. In addition to MathSBML, a number of other tools that support SBML model examination and manipulation are provided on the sbml.org website, including libSBML, a C/C++ library for reading SBML models; an SBML Toolbox for MatLab; file conversion programs; an SBML model validator and visualizer; and SBML specifications and schemas. MathSBML enables SBML file import to and export from Mathematica as well as providing an API for model manipulation and simulation.
- Published
- 2007
48. Software Infrastructure for Effective Communication and Reuse of Computational Models
- Author
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Szallasi, Zoltan, Stelling, Jörg, Periwal, Vipul, Finney, Andrew, Hucka, Michael, Bornstein, Benjamin J., Keating, Sarah M., Shapiro, Bruce E., Matthews, Joanne, Kovitz, Ben L., Schilstra, Maria J., Funahashi, Akira, Doyle, John, Kitano, Hiroaki, Szallasi, Zoltan, Stelling, Jörg, Periwal, Vipul, Finney, Andrew, Hucka, Michael, Bornstein, Benjamin J., Keating, Sarah M., Shapiro, Bruce E., Matthews, Joanne, Kovitz, Ben L., Schilstra, Maria J., Funahashi, Akira, Doyle, John, and Kitano, Hiroaki
- Abstract
Until recently, the majority of computational models in biology were implemented in custom programs and published as statements of the underlying mathematics. However, to be useful as formal embodiments of our understanding of biological systems, computational models must be put into a consistent form that can be communicated more directly between the software tools used to work with them. In this chapter, we describe the Systems Biology Markup Language (SBML), a format for representing models in a way that can be used by different software systems to communicate and exchange those models. By supporting SBML as an input and output format, different software tools can all operate on an identical representation of a model, removing opportunities for errors in translation and assuring a common starting point for analyses and simulations. We also take this opportunity to discuss some of the resources available for working with SBML as well as ongoing efforts in SBML’s continuing evolution.
- Published
- 2006
49. A Profile of Today's SBML-Compatible Software
- Author
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Hucka, Michael, primary, Bergmann, Frank T., additional, Keating, Sarah M., additional, and Smith, Lucian P., additional
- Published
- 2011
- Full Text
- View/download PDF
50. Chapter 17: Software Infrastructure for Effective Communication and Reuse of Computational Models.
- Author
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Finney, Andrew, Hucka, Michael, Bornstein, Benjamin J., Keating, Sarah M., Shapiro, Bruce E., Matthews, Joanne, Kovitz, Ben L., Schilstra, Maria J., Funahashi, Akira, Doyle, John, and Kitano, Hiroaki
- Published
- 2010
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