Model integration in computational biology: the role of reproducibility, credibility and utility

Jonathan Karr, Rahuman S. Malik-Sheriff, James Osborne, Gilberto Gonzalez-Parra, Eric Forgoston, Ruth Bowness, Yaling Liu, Robin Thompson, Winston Garira, Jacob Barhak*, John Rice, Marcella Torres*, Hana M. Dobrovolny, Tingting Tang, William Waites, James A. Glazier, James R. Faeder, Alexander Kulesza

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

9 Citations (Scopus)
24 Downloads (Pure)

Abstract

During the COVID-19 pandemic, mathematical modeling of disease transmission has become a cornerstone of key state decisions. To advance the state-of-the-art host viral modeling to handle future pandemics, many scientists working on related issues assembled to discuss the topics. These discussions exposed the reproducibility crisis that leads to inability to reuse and integrate models. This document summarizes these discussions, presents difficulties, and mentions existing efforts towards future solutions that will allow future model utility and integration. We argue that without addressing these challenges, scientists will have diminished ability to build, disseminate, and implement high-impact multi-scale modeling that is needed to understand the health crises we face.
Original languageEnglish
Article number822606
Number of pages17
JournalFrontiers in Systems Biology
Volume2
Early online date7 Mar 2022
DOIs
Publication statusPublished - 7 Mar 2022

Keywords

  • Systems Biology
  • simulation
  • reproducibility
  • crisis
  • computational modeling
  • credibility

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