Sabiia Seb
PortuguêsEspañolEnglish
Embrapa
        Busca avançada

Botão Atualizar


Botão Atualizar

Ordenar por: 

RelevânciaAutorTítuloAnoImprime registros no formato resumido
Registros recuperados: 6
Primeira ... 1 ... Última
Imagem não selecionada

Imprime registro no formato completo
Systems Biology Ontology: Update Nature Precedings
Nick Juty.
The Systems Biology Ontology (SBO) is composed of hierarchically arranged sets of controlled vocabularies that are commonly used in mathematical modelling, providing an additional layer of semantic information. We present recent developments in SBO, including the ontology's OBO Foundry status, its relationship to SBGN, and detail some of the restructuring work that has been undertaken.
Tipo: Presentation Palavras-chave: Bioinformatics; Data Standards.
Ano: 2010 URL: http://precedings.nature.com/documents/5121/version/1
Imagem não selecionada

Imprime registro no formato completo
MIRIAM Resources: a robust annotation and cross referencing framework Nature Precedings
Camille Laibe; Nick Juty; Nicolas Le Novère.
_Background_
More than ever, the era of data integration has highlighted the key requirement to reference specific data in an unambiguous and perennial way, in order to enable community-level sharing, development, exchange and reuse of information. In the field of Systems Biology, which is concerned with creating quantitative models of biological processes, these requirements have directly led to the creation of the Minimal Information Required In the Annotation of Models (MIRIAM, "http://biomodels.net/miriam/":http://biomodels.net/miriam/). MIRIAM provides a specific set of guidelines that can be implemented within any structured modelling format.

_Objectives_
To...
Tipo: Poster Palavras-chave: Bioinformatics; Data Standards.
Ano: 2010 URL: http://precedings.nature.com/documents/5128/version/1
Imagem não selecionada

Imprime registro no formato completo
Update: MIRIAM Registry and SBO Nature Precedings
Nick Juty.
We describe the MIRIAM Registry, which forms a foundation layer database upon which persistent, unambiguous and perennial identifiers of data can be built. We also describe current status and planned improvements to this system, as well as providing an update on the Systems Biology ontology since the last COMBINE meeting in Edinburgh (2010). 

Tipo: Presentation Palavras-chave: Bioinformatics; Data Standards.
Ano: 2011 URL: http://precedings.nature.com/documents/6405/version/1
Imagem não selecionada

Imprime registro no formato completo
SBML Level 3 Package Proposal: Annotation Nature Precedings
Dagmar Waltemath; Neil Swainston; Allyson L. Lister; Frank Bergmann; Ron Henkel; Stefan Hoops; Michael Hucka; Nick Juty; Sarah Keating; Christian Knuepfer; Falko Krause; Camille Laibe; Wolfram Liebermeister; Catherine Lloyd; Goksel Misirli; Marvin Schulz; Morgan Taschuk; Nicolas Le Novère.
The annotation of Systems Biology Markup Language (SBML) models with semantic terms has been supported for a number of years. The prevalence of such annotated models is growing, with repositories such as Biomodels.net and an increasing number of software tools supporting and encouraging their use and development.

With the increasing use of semantic annotations in the context of systems biology modeling has come the realization that the current Core SBML specification defining their use contains limitations that reduce the scope of metadata that can be captured in such models.

SBML Level 3 provides the facility to propose and develop optional extensions to the Core specification. One such...
Tipo: Manuscript Palavras-chave: Bioinformatics; Data Standards.
Ano: 2011 URL: http://precedings.nature.com/documents/5610/version/1
Imagem não selecionada

Imprime registro no formato completo
Ontologies for use in Systems Biology: SBO, KiSAO and TEDDY Nature Precedings
Nick Juty; Nicolas Le Novère; Dagmar Waltemath; Christian Knuepfer.
The use of computational modelling in the description and analysis of biological systems is at the heart of Systems Biology. Besides the information stored in a core model, there is increasingly a need to provide additional semantic information: to identify model components, to assist in biological interpretation of models, to define simulation conditions and to describe simulation results. This information deficit can be addressed through the use of ontologies. We describe here three ontologies created specifically to address the needs of the Systems Biology community in each sub-division, and illustrate their practical use with the 'Repressilator' model (Elowitz and Leibler, 2000).
Tipo: Poster Palavras-chave: Bioinformatics; Data Standards.
Ano: 2010 URL: http://precedings.nature.com/documents/5122/version/1
Imagem não selecionada

Imprime registro no formato completo
Kinetic Simulation Algorithm Ontology Nature Precedings
Anna Zhukova; Dagmar Waltemath; Nick Juty; Camille Laibe; Nicolas Le Novère.
To enable the accurate and repeatable execution of a computational simulation task, it is important to identify both the algorithm used and the initial setup. These minimum information requirements are described by the MIASE guidelines. Since the details of some algorithms are not always publicly available, and many are implemented only in a limited number of simulation tools, it is crucial to identify alternative algorithms with similar characteristics that may be used to provide comparable results in an equivalent simulation experiment. The Kinetic Simulation Algorithm Ontology (KiSAO) was developed to address this issue by describing existing algorithms and their inter-relationships through their characteristics and parameters. The use of KiSAO in...
Tipo: Presentation Palavras-chave: Bioinformatics; Data Standards.
Ano: 2011 URL: http://precedings.nature.com/documents/6330/version/1
Registros recuperados: 6
Primeira ... 1 ... Última
 

Empresa Brasileira de Pesquisa Agropecuária - Embrapa
Todos os direitos reservados, conforme Lei n° 9.610
Política de Privacidade
Área restrita

Embrapa
Parque Estação Biológica - PqEB s/n°
Brasília, DF - Brasil - CEP 70770-901
Fone: (61) 3448-4433 - Fax: (61) 3448-4890 / 3448-4891 SAC: https://www.embrapa.br/fale-conosco

Valid HTML 4.01 Transitional