Literature DB >> 30256901

SemGen: a tool for semantics-based annotation and composition of biosimulation models.

Maxwell L Neal1, Christopher T Thompson2, Karam G Kim3, Ryan C James3, Daniel L Cook3, Brian E Carlson2, John H Gennari3.   

Abstract

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.
© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Year:  2019        PMID: 30256901      PMCID: PMC6499248          DOI: 10.1093/bioinformatics/bty829

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  16 in total

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  9 in total

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