Model Integration in Computational Biology: The Role of Reproducibility, Credibility and Utility

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; Glazier, James A.; Faeder, James R.; Kulesza, Alexander

Publication

Model Integration in Computational Biology: The Role of Reproducibility, Credibility and Utility

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; Glazier, James A.; Faeder, James R.; Kulesza, Alexander

Publisher

Frontiers Media SA

Date

2022

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.