4.7 Review

Publishing reproducible dynamic kinetic models

Journal

BRIEFINGS IN BIOINFORMATICS
Volume 22, Issue 3, Pages -

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbaa152

Keywords

systems biology; kinetic modeling; SBML; standards; reproducibility

Funding

  1. National Institute of General Medical Sciences
  2. National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health [R01GM123032, P41GM109824]
  3. National Science Foundation Civil, Mechanical and Manufacturing Innovation award [1933453]
  4. Directorate For Engineering
  5. Div Of Civil, Mechanical, & Manufact Inn [1933453] Funding Source: National Science Foundation

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The article highlights the importance of publishing repeatable and reproducible computational models in computational biology, specifically focusing on issues in the systems biology field. It discusses the current landscape in terms of software tools, model repositories, standards, and best practices, as well as potential future remedies to improve reproducibility in scientific research.
Publishing repeatable and reproducible computational models is a crucial aspect of the scientific method in computational biology and one that is often forgotten in the rush to publish. The pressures of academic life and the lack of any reward system at institutions, granting agencies and journals means that publishing reproducible science is often either non-existent or, at best, presented in the form of an incomplete description. In the article, we will focus on repeatability and reproducibility in the systems biology field where a great many published models cannot be reproduced and in many cases even repeated. This review describes the current landscape of software tooling, model repositories, model standards and best practices for publishing repeatable and reproducible kinetic models. The review also discusses possible future remedies including working more closely with journals to help reviewers and editors ensure that published kinetic models are at minimum, repeatable. Contact: hsauro@uw.edu

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