Literature DB >> 16333295

Minimum information requested in the annotation of biochemical models (MIRIAM).

Nicolas Le Novère1, Andrew Finney, Michael Hucka, Upinder S Bhalla, Fabien Campagne, Julio Collado-Vides, Edmund J Crampin, Matt Halstead, Edda Klipp, Pedro Mendes, Poul Nielsen, Herbert Sauro, Bruce Shapiro, Jacky L Snoep, Hugh D Spence, Barry L Wanner.   

Abstract

Most of the published quantitative models in biology are lost for the community because they are either not made available or they are insufficiently characterized to allow them to be reused. The lack of a standard description format, lack of stringent reviewing and authors' carelessness are the main causes for incomplete model descriptions. With today's increased interest in detailed biochemical models, it is necessary to define a minimum quality standard for the encoding of those models. We propose a set of rules for curating quantitative models of biological systems. These rules define procedures for encoding and annotating models represented in machine-readable form. We believe their application will enable users to (i) have confidence that curated models are an accurate reflection of their associated reference descriptions, (ii) search collections of curated models with precision, (iii) quickly identify the biological phenomena that a given curated model or model constituent represents and (iv) facilitate model reuse and composition into large subcellular models.

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Mesh:

Year:  2005        PMID: 16333295     DOI: 10.1038/nbt1156

Source DB:  PubMed          Journal:  Nat Biotechnol        ISSN: 1087-0156            Impact factor:   54.908


  192 in total

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5.  Systems Biology Markup Language (SBML) Level 2 Version 5: Structures and Facilities for Model Definitions.

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6.  The Systems Biology Markup Language (SBML): Language Specification for Level 3 Version 1 Core.

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Review 9.  Consistent design schematics for biological systems: standardization of representation in biological engineering.

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Journal:  J R Soc Interface       Date:  2009-06-03       Impact factor: 4.118

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Journal:  Nat Biotechnol       Date:  2013-03-03       Impact factor: 54.908

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