375 results on '"Hucka Michael"'
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2. 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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3. 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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4. 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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5. 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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6. 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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7. 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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8. 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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9. 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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10. Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2016
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Schreiber Falk, Bader Gary D., Gleeson Padraig, Golebiewski Martin, Hucka Michael, Novère Nicolas Le, Myers Chris, Nickerson David, Sommer Björn, and Waltemath Dagmar
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Biotechnology ,TP248.13-248.65 - Abstract
Standards are essential to the advancement of science and technology. In systems and synthetic biology, numerous standards and associated tools have been developed over the last 16 years. This special issue of the Journal of Integrative Bioinformatics aims to support the exchange, distribution and archiving of these standards, as well as to provide centralised and easily citable access to them.
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- 2016
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11. SBML Level 3 package: Groups, Version 1 Release 1
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Hucka Michael and Smith Lucian P.
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Biotechnology ,TP248.13-248.65 - Abstract
Biological models often contain components that have relationships with each other, or that modelers want to treat as belonging to groups with common characteristics or shared metadata. The SBML Level 3 Version 1 Core specification does not provide a n explicit mechanism for expressing such relationships, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactical constructs. The SBML Groups package for SBML Level 3 adds the necessary features to SBML to allow grouping of model components to be expressed. Such groups do not affect the mathematical interpretation of a model, but they do provide a way to add information that can be useful for modelers and software tools. The SBML Groups package enables a modeler to include definitions of groups and nested groups, each of which may be annotated to convey why that group was created, and what it represents.
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- 2016
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12. 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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13. 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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14. 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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15. SBML Level 3 package: Hierarchical Model Composition, Version 1 Release 3
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Smith Lucian P., Hucka Michael, Hoops Stefan, Finney Andrew, Ginkel Martin, Myers Chris J., Moraru Ion, and Liebermeister Wolfram
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Biotechnology ,TP248.13-248.65 - Abstract
Constructing a model in a hierarchical fashion is a natural approach to managing model complexity, and offers additional opportunities such as the potential to re-use model components. The SBML Level 3 Version 1 Core specification does not directly provide a mechanism for defining hierarchical models, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactical constructs. The SBML Hierarchical Model Composition package for SBML Level 3 adds the necessary features to SBML to support hierarchical modeling. The package enables a modeler to include submodels within an enclosing SBML model, delete unneeded or redundant elements of that submodel, replace elements of that submodel with element of the containing model, and replace elements of the containing model with elements of the submodel. In addition, the package defines an optional “port” construct, allowing a model to be defined with suggested interfaces between hierarchical components; modelers can chose to use these interfaces, but they are not required to do so and can still interact directly with model elements if they so chose. Finally, the SBML Hierarchical Model Composition package is defined in such a way that a hierarchical model can be “flattened” to an equivalent, non-hierarchical version that uses only plain SBML constructs, thus enabling software tools that do not yet support hierarchy to nevertheless work with SBML hierarchical models.
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- 2015
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16. 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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17. Specifications of Standards in Systems and Synthetic Biology
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Schreiber Falk, Bader Gary D., Golebiewski Martin, Hucka Michael, Kormeier Benjamin, Le Novère Nicolas, Myers Chris, Nickerson David, Sommer Björn, Waltemath Dagmar, and Weise Stephan
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Biotechnology ,TP248.13-248.65 - Abstract
Standards shape our everyday life. From nuts and bolts to electronic devices and technological processes, standardised products and processes are all around us. Standards have technological and economic benefits, such as making information exchange, production, and services more efficient. However, novel, innovative areas often either lack proper standards, or documents about standards in these areas are not available from a centralised platform or formal body (such as the International Standardisation Organisation).
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- 2015
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18. Nine Best Practices for Research Software Registries and Repositories: A Concise Guide
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Registries, Task Force on Best Practices for Software, Monteil, Alain, Gonzalez-Beltran, Alejandra, Ioannidis, Alexandros, Allen, Alice, Lee, Allen, Bandrowski, Anita, Wilson, Bruce E., Mecum, Bryce, Du, Cai Fan, Robinson, Carly, Garijo, Daniel, Katz, Daniel S., Long, David, Milliken, Genevieve, Ménager, Hervé, Hausman, Jessica, Spaaks, Jurriaan H., Fenlon, Katrina, Vanderbilt, Kristin, Hwang, Lorraine, Davis, Lynn, Fenner, Martin, Crusoe, Michael R., Hucka, Michael, Wu, Mingfang, Hong, Neil Chue, Teuben, Peter, Stall, Shelley, Druskat, Stephan, Carnevale, Ted, and Morrell, Thomas
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Computer Science - Digital Libraries ,Computer Science - Computers and Society - Abstract
Scientific software registries and repositories serve various roles in their respective disciplines. These resources improve software discoverability and research transparency, provide information for software citations, and foster preservation of computational methods that might otherwise be lost over time, thereby supporting research reproducibility and replicability. However, developing these resources takes effort, and few guidelines are available to help prospective creators of registries and repositories. To address this need, we present a set of nine best practices that can help managers define the scope, practices, and rules that govern individual registries and repositories. These best practices were distilled from the experiences of the creators of existing resources, convened by a Task Force of the FORCE11 Software Citation Implementation Working Group during the years 2019-2020. We believe that putting in place specific policies such as those presented here will help scientific software registries and repositories better serve their users and their disciplines., Comment: 18 pages
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- 2020
19. Software that goes with the flow in systems biology
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Le Novère Nicolas and Hucka Michael
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Biology (General) ,QH301-705.5 - Abstract
Abstract A recent article in BMC Bioinformatics describes new advances in workflow systems for computational modeling in systems biology. Such systems can accelerate, and improve the consistency of, modeling through automation not only at the simulation and results-production stages, but also at the model-generation stage. Their work is a harbinger of the next generation of more powerful software for systems biologists. See research article: http://www.biomedcentral.com/1471-2105/11/582/abstract/ Ever since the rise of systems biology at the end of the last century, mathematical representations of biological systems and their activities have flourished. They are being used to describe everything from biomolecular networks, such as gene regulation, metabolic processes and signaling pathways, at the lowest biological scales, to tissue growth and differentiation, drug effects, environmental interactions, and more. A very active area in the field has been the development of techniques that facilitate the construction, analysis and dissemination of computational models. The heterogeneous, distributed nature of most data resources today has increased not only the opportunities for, but also the difficulties of, developing software systems to support these tasks. The work by Li et al. 1 published in BMC Bioinformatics represents a promising evolutionary step forward in this area. They describe a workflow system - a visual software environment enabling a user to create a connected set of operations to be performed sequentially using seperate tools and resources. Their system uses third-party data resources accessible over the Internet to elaborate and parametrize (that is, assign parameter values to) computational models in a semi-automated manner. In Li et al.'s work, the authors point towards a promising future for computational modeling and simultaneously highlight some of the difficulties that need to be overcome before we get there.
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- 2010
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20. 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
21. 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
22. 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
23. Software search is not a science, even among scientists: A survey of how scientists and engineers find software
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Hucka, Michael and Graham, Matthew J.
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Computer Science - Computers and Society ,Computer Science - Software Engineering - Abstract
Improved software discovery is a prerequisite for greater software reuse: after all, if someone cannot find software for a particular task, they cannot reuse it. Understanding people's approaches and preferences when they look for software could help improve facilities for software discovery. We surveyed people working in several scientific and engineering fields to better understand their approaches and selection criteria. We found that even among highly-trained people, the rudimentary approaches of relying on general Web searches, the opinions of colleagues, and the literature were still the most commonly used. However, those who were involved in software development differed from nondevelopers in their use of social help sites, software project repositories, software catalogs, and organization-specific mailing lists or forums. For example, software developers in our sample were more likely to search in community sites such as Stack Overflow even when seeking ready-to-run software rather than source code, and likewise, asking colleagues was significantly more important when looking for ready-to-run software. Our survey also provides insight into the criteria that matter most to people when they are searching for ready-to-run software. Finally, our survey also identifies some factors that can prevent people from finding software.
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- 2016
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24. Systems Biology Markup Language (SBML)
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Hucka, Michael, primary
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- 2022
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25. One file to share them all: Using the COMBINE Archive and the OMEX format to share all information about a modeling project
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Bergmann, Frank T., Adams, Richard, Moodie, Stuart, Cooper, Jonathan, Glont, Mihai, Golebiewski, Martin, Hucka, Michael, Laibe, Camille, Miller, Andrew K., Nickerson, David P., Olivier, Brett G., Rodriguez, Nicolas, Sauro, Herbert M., Scharm, Martin, Soiland-Reyes, Stian, Waltemath, Dagmar, Yvon, Florent, and Novère, Nicolas Le
- Subjects
Computer Science - Digital Libraries ,Quantitative Biology - Molecular Networks - Abstract
Background: With the ever increasing use of computational models in the biosciences, the need to share models and reproduce the results of published studies efficiently and easily is becoming more important. To this end, various standards have been proposed that can be used to describe models, simulations, data or other essential information in a consistent fashion. These constitute various separate components required to reproduce a given published scientific result. Results: We describe the Open Modeling EXchange format (OMEX). Together with the use of other standard formats from the Computational Modeling in Biology Network (COMBINE), OMEX is the basis of the COMBINE Archive, a single file that supports the exchange of all the information necessary for a modeling and simulation experiment in biology. An OMEX file is a ZIP container that includes a manifest file, listing the content of the archive, an optional metadata file adding information about the archive and its content, and the files describing the model. The content of a COMBINE Archive consists of files encoded in COMBINE standards whenever possible, but may include additional files defined by an Internet Media Type. Several tools that support the COMBINE Archive are available, either as independent libraries or embedded in modeling software. Conclusions: The COMBINE Archive facilitates the reproduction of modeling and simulation experiments in biology by embedding all the relevant information in one file. Having all the information stored and exchanged at once also helps in building activity logs and audit trails. We anticipate that the COMBINE Archive will become a significant help for modellers, as the domain moves to larger, more complex experiments such as multi-scale models of organs, digital organisms, and bioengineering., Comment: 3 figures, 1 table
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- 2014
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26. JSBML 1.0: providing a smorgasbord of options to encode systems biology models.
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Rodriguez, Nicolas, Thomas, Alex, Watanabe, Leandro, Vazirabad, Ibrahim Y, Kofia, Victor, Gómez, Harold F, Mittag, Florian, Matthes, Jakob, Rudolph, Jan, Wrzodek, Finja, Netz, Eugen, Diamantikos, Alexander, Eichner, Johannes, Keller, Roland, Wrzodek, Clemens, Fröhlich, Sebastian, Lewis, Nathan E, Myers, Chris J, Le Novère, Nicolas, Palsson, Bernhard Ø, Hucka, Michael, and Dräger, Andreas
- Subjects
Systems Biology ,Models ,Biological ,Computer Simulation ,Software ,Programming Languages ,Networking and Information Technology R&D ,Bioinformatics ,Mathematical Sciences ,Biological Sciences ,Information and Computing Sciences - Abstract
UnlabelledJSBML, the official pure Java programming library for the Systems Biology Markup Language (SBML) format, has evolved with the advent of different modeling formalisms in systems biology and their ability to be exchanged and represented via extensions of SBML. JSBML has matured into a major, active open-source project with contributions from a growing, international team of developers who not only maintain compatibility with SBML, but also drive steady improvements to the Java interface and promote ease-of-use with end users.Availability and implementationSource code, binaries and documentation for JSBML can be freely obtained under the terms of the LGPL 2.1 from the website http://sbml.org/Software/JSBML. More information about JSBML can be found in the user guide at http://sbml.org/Software/JSBML/docs/.Contactjsbml-development@googlegroups.com or andraeger@eng.ucsd.eduSupplementary informationSupplementary data are available at Bioinformatics online.
- Published
- 2015
27. 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
- Subjects
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
- Published
- 2013
28. Large-scale generation of computational models from biochemical pathway maps
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Büchel, Finja, Rodriguez, Nicolas, Swainston, Neil, Wrzodek, Clemens, Czauderna, Tobias, Keller, Roland, Mittag, Florian, Schubert, Michael, Glont, Mihai, Golebiewski, Martin, van Iersel, Martijn, Keating, Sarah, Rall, Matthias, Wybrow, Michael, Hermjakob, Henning, Hucka, Michael, Kell, Douglas B., Müller, Wolfgang, Mendes, Pedro, Zell, Andreas, Chaouiya, Claudine, Saez-Rodriguez, Julio, Schreiber, Falk, Laibe, Camille, Dräger, Andreas, and Novère, Nicolas Le
- Subjects
Quantitative Biology - Molecular Networks - Abstract
Background: Systems biology projects and omics technologies have led to a growing number of biochemical pathway reconstructions. However, mathematical models are still most often created de novo, based on reading the literature and processing pathway data manually. Results: To increase the efficiency with which such models can be created, we automatically generated mathematical models from pathway representations using a suite of freely available software. We produced models that combine data from KEGG PATHWAY, BioCarta, MetaCyc and SABIO-RK; According to the source data, three types of models are provided: kinetic, logical and constraint-based. All models are encoded using SBML Core and Qual packages, and available through BioModels Database. Each model contains the list of participants, the interactions, and the relevant mathematical constructs, but, in most cases, no meaningful parameter values. Most models are also available as easy to understand graphical SBGN maps. Conclusions: to date, the project has resulted in more than 140000 models freely available. We believe this resource can tremendously accelerate the development of mathematical models by providing initial starting points ready for parametrization., Comment: 29 pages, 8 figures
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- 2013
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29. Path2Models: large-scale generation of computational models from biochemical pathway maps
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Büchel, Finja, Rodriguez, Nicolas, Swainston, Neil, Wrzodek, Clemens, Czauderna, Tobias, Keller, Roland, Mittag, Florian, Schubert, Michael, Glont, Mihai, Golebiewski, Martin, van Iersel, Martijn, Keating, Sarah, Rall, Matthias, Wybrow, Michael, Hermjakob, Henning, Hucka, Michael, Kell, Douglas B, Müller, Wolfgang, Mendes, Pedro, Zell, Andreas, Chaouiya, Claudine, Saez-Rodriguez, Julio, Schreiber, Falk, Laibe, Camille, Dräger, Andreas, and Le Novère, Nicolas
- Abstract
Abstract Background Systems biology projects and omics technologies have led to a growing number of biochemical pathway models and reconstructions. However, the majority of these models are still created de novo, based on literature mining and the manual processing of pathway data. Results To increase the efficiency of model creation, the Path2Models project has automatically generated mathematical models from pathway representations using a suite of freely available software. Data sources include KEGG, BioCarta, MetaCyc and SABIO-RK. Depending on the source data, three types of models are provided: kinetic, logical and constraint-based. Models from over 2 600 organisms are encoded consistently in SBML, and are made freely available through BioModels Database at http://www.ebi.ac.uk/biomodels-main/path2models. Each model contains the list of participants, their interactions, the relevant mathematical constructs, and initial parameter values. Most models are also available as easy-to-understand graphical SBGN maps. Conclusions To date, the project has resulted in more than 140 000 freely available models. Such a resource can tremendously accelerate the development of mathematical models by providing initial starting models for simulation and analysis, which can be subsequently curated and further parameterized.
- Published
- 2013
30. Towards NeuroML: Model Description Methods for Collaborative Modelling in Neuroscience
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Goddard, Nigel H., Hucka, Michael, Howell, Fred, Cornelis, Hugo, Shankar, Kavita, and Beeman, David
- Published
- 2001
31. Data Management in Computational Systems Biology: Exploring Standards, Tools, Databases, and Packaging Best Practices
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Stanford, Natalie J., primary, Scharm, Martin, additional, Dobson, Paul D., additional, Golebiewski, Martin, additional, Hucka, Michael, additional, Kothamachu, Varun B., additional, Nickerson, David, additional, Owen, Stuart, additional, Pahle, Jürgen, additional, Wittig, Ulrike, additional, Waltemath, Dagmar, additional, Goble, Carole, additional, Mendes, Pedro, additional, and Snoep, Jacky, additional
- Published
- 2019
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32. Approximate Spatial Layout Processing in Early Vision
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Hucka, Michael and Kaplan, Stephan
- Published
- 1996
33. Systems Biology Markup Language (SBML)
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Hucka, Michael, Dubitzky, Werner, editor, Wolkenhauer, Olaf, editor, Cho, Kwang-Hyun, editor, and Yokota, Hiroki, editor
- Published
- 2013
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34. Trends and Tools for Modeling in Modern Biology
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Hucka, Michael, Schaff, James, Govindjee, editor, Laisk, Agu, editor, and Nedbal, Ladislav, editor
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- 2009
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35. 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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36. Correction to: Meeting report from the fourth meeting of the Computational Modeling in Biology Network (COMBINE)
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Waltemath, Dagmar, Bergmann, Frank T., Chaouiya, Claudine, Czauderna, Tobias, Gleeson, Padraig, Goble, Carole, Golebiewski, Martin, Hucka, Michael, Juty, Nick, Krebs, Olga, Le Novère, Nicolas, Mi, Huaiyu, Moraru, Ion I., Myers, Chris J., Nickerson, David, Olivier, Brett G., Rodriguez, Nicolas, Schreiber, Falk, Smith, Lucian, Zhang, Fengkai, and Bonnet, Eric
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- 2018
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37. Modeling the E. coli cell: The need for computing, cooperation, and consortia
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Wanner, Barry L., Finney, Andrew, Hucka, Michael, Alberghina, Lila, editor, and Westerhoff, H.V., editor
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- 2005
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38. The Modeler’s Workspace : Making Model-Based Studies of the Nervous System More Accessible
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Hucka, Michael, Shankar, Kavita, Beeman, David, Bower, James M., and Ascoli, Giorgio A., editor
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- 2002
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39. Systems Biology Markup Language (SBML)
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Hucka, Michael, Jaeger, Dieter, editor, and Jung, Ranu, editor
- Published
- 2015
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- View/download PDF
40. Meeting report from the fourth meeting of the Computational Modeling in Biology Network (COMBINE)
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Waltemath, Dagmar, Bergmann, Frank T., Chaouiya, Claudine, Czauderna, Tobias, Gleeson, Padraig, Goble, Carole, Golebiewski, Martin, Hucka, Michael, Juty, Nick, Krebs, Olga, Le Novère, Nicolas, Mi, Huaiyu, Moraru, Ion I., Myers, Chris J., Nickerson, David, Olivier, Brett G., Rodriguez, Nicolas, Schreiber, Falk, Smith, Lucian, Zhang, Fengkai, and Bonnet, Eric
- Published
- 2014
- Full Text
- View/download PDF
41. BioModels: ten-year anniversary
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Chelliah, Vijayalakshmi, Juty, Nick, Ajmera, Ishan, Ali, Raza, Dumousseau, Marine, Glont, Mihai, Hucka, Michael, Jalowicki, Gaël, Keating, Sarah, Knight-Schrijver, Vincent, Lloret-Villas, Audald, Natarajan, Kedar Nath, Pettit, Jean-Baptiste, Rodriguez, Nicolas, Schubert, Michael, Wimalaratne, Sarala M., Zhao, Yangyang, Hermjakob, Henning, Le Novère, Nicolas, and Laibe, Camille
- Published
- 2015
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42. Do genome‐scale models need exact solvers or clearer standards?
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Ebrahim, Ali, Almaas, Eivind, Bauer, Eugen, Bordbar, Aarash, Burgard, Anthony P, Chang, Roger L, Dräger, Andreas, Famili, Iman, Feist, Adam M, Fleming, Ronan MT, Fong, Stephen S, Hatzimanikatis, Vassily, Herrgård, Markus J, Holder, Allen, Hucka, Michael, Hyduke, Daniel, Jamshidi, Neema, Lee, Sang Yup, Le Novère, Nicolas, Lerman, Joshua A, Lewis, Nathan E, Ma, Ding, Mahadevan, Radhakrishnan, Maranas, Costas, Nagarajan, Harish, Navid, Ali, Nielsen, Jens, Nielsen, Lars K, Nogales, Juan, Noronha, Alberto, Pal, Csaba, Palsson, Bernhard O, Papin, Jason A, Patil, Kiran R, Price, Nathan D, Reed, Jennifer L, Saunders, Michael, Senger, Ryan S, Sonnenschein, Nikolaus, Sun, Yuekai, and Thiele, Ines
- Published
- 2015
- Full Text
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43. 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
44. Systems Biology Markup Language (SBML)
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Hucka, Michael, primary
- Published
- 2013
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45. Trends and Tools for Modeling in Modern Biology
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Hucka, Michael, primary and Schaff, James, additional
- Published
- 2009
- Full Text
- View/download PDF
46. JSBML: a flexible Java library for working with SBML
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Dräger, Andreas, Rodriguez, Nicolas, Dumousseau, Marine, Dörr, Alexander, Wrzodek, Clemens, Le Novère, Nicolas, Zell, Andreas, and Hucka, Michael
- Published
- 2011
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47. Software Infrastructure for Effective Communication and Reuse of Computational Models
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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
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- 2006
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48. SBML2LATEX: Conversion of SBML files into human-readable reports
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Dräger, Andreas, Planatscher, Hannes, Motsou Wouamba, Dieudonné, Schröder, Adrian, Hucka, Michael, Endler, Lukas, Golebiewski, Martin, Müller, Wolfgang, and Zell, Andreas
- Published
- 2009
49. LibSBML: an API Library for SBML
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Bornstein, Benjamin J., Keating, Sarah M., Jouraku, Akiya, and Hucka, Michael
- Published
- 2008
50. Harmonizing semantic annotations for computational models in biology
- Author
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Neal, Maxwell Lewis and Hucka, Michael
- Abstract
Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation.
- Published
- 2019
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