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

Karr, Jonathan and Malik-Sheriff, Rahuman S. and Osborne, James and Gonzalez-Parra, Gilberto and Forgoston, Eric and Bowness, Ruth and Liu, Yaling and Thompson, Robin and Garira, Winston and Barhak, Jacob and Rice, John and Torres, Marcella and Dobrovolny, Hana M. and Tang, Tingting and Waites, William and Glazier, James A. and Faeder, James R. and Kulesza, Alexander (2022) Model integration in computational biology : the role of reproducibility, credibility and utility. Frontiers in Systems Biology, 2. 822606. ISSN 2674-0702 (https://doi.org/10.3389/fsysb.2022.822606)

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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.

ORCID iDs

Karr, Jonathan, Malik-Sheriff, Rahuman S., Osborne, James, Gonzalez-Parra, Gilberto, Forgoston, Eric, Bowness, Ruth, Liu, Yaling, Thompson, Robin, Garira, Winston, Barhak, Jacob, Rice, John, Torres, Marcella, Dobrovolny, Hana M., Tang, Tingting, Waites, William ORCID logoORCID: https://orcid.org/0000-0002-7759-6805, Glazier, James A., Faeder, James R. and Kulesza, Alexander;
CORE (COnnecting REpositories)