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WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions
Filetype[PDF - 768.26 KB]


Details:
  • Pubmed ID:
    25231498
  • Pubmed Central ID:
    PMC4165886
  • Funding:
    1P50GM107615/GM/NIGMS NIH HHS/United States
    5DP1LM01150-05/DP/NCCDPHP CDC HHS/United States
    DP1 LM011510/LM/NLM NIH HHS/United States
    DP1 OD006413/OD/NIH HHS/United States
    P50 GM107615/GM/NIGMS NIH HHS/United States
  • Document Type:
  • Collection(s):
  • Description:
    Mechanistic 'whole-cell' models are needed to develop a complete understanding of cell physiology. However, extracting biological insights from whole-cell models requires running and analyzing large numbers of simulations. We developed WholeCellSimDB, a database for organizing whole-cell simulations. WholeCellSimDB was designed to enable researchers to search simulation metadata to identify simulations for further analysis, and quickly slice and aggregate simulation results data. In addition, WholeCellSimDB enables users to share simulations with the broader research community. The database uses a hybrid relational/hierarchical data format architecture to efficiently store and retrieve both simulation setup metadata and results data. WholeCellSimDB provides a graphical Web-based interface to search, browse, plot and export simulations; a JavaScript Object Notation (JSON) Web service to retrieve data for Web-based visualizations; a command-line interface to deposit simulations; and a Python API to retrieve data for advanced analysis. Overall, we believe WholeCellSimDB will help researchers use whole-cell models to advance basic biological science and bioengineering.|http://www.wholecellsimdb.org SOURCE CODE REPOSITORY: URL: http://github.com/CovertLab/WholeCellSimDB.