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SemGen: a tool for semantics-based annotation and composition of biosimulation models.
Neal, Maxwell L; Thompson, Christopher T; Kim, Karam G; James, Ryan C; Cook, Daniel L; Carlson, Brian E; Gennari, John H.
Afiliación
  • Neal ML; Seattle Children's Research Institute, Center for Global Infectious Disease Research, Seattle, WA, USA.
  • Thompson CT; Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA.
  • Kim KG; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA.
  • James RC; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA.
  • Cook DL; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA.
  • Carlson BE; Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA.
  • Gennari JH; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA.
Bioinformatics ; 35(9): 1600-1602, 2019 05 01.
Article en En | MEDLINE | ID: mdl-30256901
SUMMARY: As the number and complexity of biosimulation models grows, so do demands for tools that can help users understand models and compose more comprehensive and accurate systems from existing models. SemGen is a tool for semantics-based annotation and composition of biosimulation models designed to address this demand. A key SemGen capability is to decompose and then integrate models across existing model exchange formats including SBML and CellML. To support this capability, we use semantic annotations to explicitly capture the underlying biological and physical meanings of the entities and processes that are modeled. SemGen leverages annotations to expose a model's biological and computational architecture and to help automate model composition. AVAILABILITY AND IMPLEMENTATION: SemGen is freely available at https://github.com/SemBioProcess/SemGen. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Semántica / Programas Informáticos Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Semántica / Programas Informáticos Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos
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