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Tellurium notebooks—An environment for reproducible dynamical modeling in systems biology.

Authors :
Medley, J. Kyle
Choi, Kiri
König, Matthias
Smith, Lucian
Gu, Stanley
Hellerstein, Joseph
Sealfon, Stuart C.
Sauro, Herbert M.
Source :
PLoS Computational Biology; 6/15/2018, Vol. 14 Issue 6, p1-24, 24p, 1 Diagram, 2 Charts, 4 Graphs
Publication Year :
2018

Abstract

The considerable difficulty encountered in reproducing the results of published dynamical models limits validation, exploration and reuse of this increasingly large biomedical research resource. To address this problem, we have developed Tellurium Notebook, a software system for model authoring, simulation, and teaching that facilitates building reproducible dynamical models and reusing models by 1) providing a notebook environment which allows models, Python code, and narrative to be intermixed, 2) supporting the COMBINE archive format during model development for capturing model information in an exchangeable format and 3) enabling users to easily simulate and edit public COMBINE-compliant models from public repositories to facilitate studying model dynamics, variants and test cases. Tellurium Notebook, a Python–based Jupyter–like environment, is designed to seamlessly inter-operate with these community standards by automating conversion between COMBINE standards formulations and corresponding in–line, human–readable representations. Thus, Tellurium brings to systems biology the strategy used by other literate notebook systems such as Mathematica. These capabilities allow users to edit every aspect of the standards–compliant models and simulations, run the simulations in–line, and re–export to standard formats. We provide several use cases illustrating the advantages of our approach and how it allows development and reuse of models without requiring technical knowledge of standards. Adoption of Tellurium should accelerate model development, reproducibility and reuse. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1553734X
Volume :
14
Issue :
6
Database :
Complementary Index
Journal :
PLoS Computational Biology
Publication Type :
Academic Journal
Accession number :
130188489
Full Text :
https://doi.org/10.1371/journal.pcbi.1006220