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1.
J Integr Bioinform ; 12(2): 270, 2015 Sep 04.
Article in English | MEDLINE | ID: mdl-26528568

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. The SBML Qualitative Models package for SBML Level 3 adds features so that qualitative models can be directly and explicitly encoded. The approach taken in this package is essentially based on the definition of regulatory or influence graphs. The SBML Qualitative Models package defines the structure and syntax necessary to describe qualitative models that associate discrete levels of activities with entity pools and the transitions between states that describe the processes involved. This is particularly suited to logical models (Boolean or multi-valued) and some classes of Petri net models can be encoded with the approach.


Subject(s)
Computer Graphics/standards , Models, Biological , Programming Languages , Proteome/metabolism , Signal Transduction/physiology , Systems Biology/standards , Animals , Biological Ontologies , Datasets as Topic/standards , Documentation/standards , Guidelines as Topic/standards , Humans , Information Storage and Retrieval/standards , Internationality
2.
BMC Syst Biol ; 7: 135, 2013 Dec 10.
Article in English | MEDLINE | ID: mdl-24321545

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 Systems 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 collective effort to define 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 analyse qualitative models. CONCLUSIONS: 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.


Subject(s)
Models, Biological , Programming Languages , Animals , Cells/cytology , Cells/metabolism , Epidermal Growth Factor/metabolism , Internet , Signal Transduction , Tumor Necrosis Factor-alpha/metabolism
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