modelRxiv: A platform for the dissemination and interactive display of models

Abstract

Modeling the dynamics of biological processes is ubiquitous across the ecological and evolutionary disciplines. However, the increasing complexity of these models poses a significant challenge to the dissemination of model-derived results. With the existing standards of scientific publishing, most often only a small subset of model results are generated, presented in static figures or tables, and made available to the scientific community. Further exploration of the parameter space of a model, investigation of possible variations of a model, and validation of the results in relation to model assumptions commonly rely on local deployment of code supplied by the authors. While releasing model code is a publication requirement for most scientific journals, there are currently no standardized protocols or coding-language requirements. Deploying models locally poses a technical challenge due to the specific framework and environment in which a model was developed, and can preclude model validation and exploration by readers and reviewers. To address this issue, we developed a platform that serves as an interactive repository of biological models, called modelRxiv (https://modelrxiv.org). The platform provides a unified interface for the analysis of models developed in multiple programming languages but does not require any technical understanding of the model implementation. To reduce model computation time, the platform allows users to pool computational resources available to them, including lab workstations, clusters and cloud services. By making published models accessible, this platform promises to significantly improve the accessibility, reproducibility and validation of ecological and evolutionary models.

Toward a unified theory of microbially-mediated invasion

“…(1). A user-friendly version of the code is made publicly available on the modelRxiv platform (Harris et al, 2022) (https://modelrxiv.org/model/YfndNX), and can be used for this purpose. In SI I we also provide more details on the outcomes of each scenario depending on parameter values, espe-cially on different outcomes observed when varying the competitive effect of one species on another (i.e., the magnitude of the c parameters), or the degree of mutualism of the host (from obligate to facultative).…”

“…In this sense, our framework can be regarded as a helpful tool to explore possible microbially mediated invasion dynamics. In particular, parametrization based on realistic biological scenarios may provide insights into possible outcomes through numerical simulations (e.g., through the tool we provide on the modelRxiv platform, Harris et al (2022)). Future model parametrization may utilize phylogenetic or ecological similarity as predictors of the amount of microbial sharing (Vacher et al, 2010; Bufford et al, 2016; Parker et al, 2015; Gilbert and Parker, 2016; Davison et al, 2015), together with other traits related to the invasiveness and invasibility of native and invasive species (Hoeksema et al, 2020; Traveset and Richardson, 2014; Litchman, 2010), such as their dependence on the symbiosis (Vogelsang and Bever, 2009; Klironomos, 2003).…”

Rescue by gene swamping as a gene drive deployment strategy

“…For simplicity and coherence, we define population 1 as the 'target population' that we aim to suppress and where the gene drive is deployed, and population 2 as the 'non-target population'. The model is implemented and available on the modelRxiv platform [21], where all results can be regenerated and the model can be re-parameterized (https://modelrxiv.org/model/yoKkSv).…”

“…To facilitate further exploration of our results, we uploaded the model to the platform modelRxiv, which allows visualization and analysis of models through a simple user interface ( [21]; https://modelrxiv.org/ model/yoKkSv and https://modelrxiv.org/model/k8h5M6). In this platform, the results can be regenerated and the model can be re-parameterized (Fig.…”