GreenSloth: a curated database and executable platform for mechanistic photosynthesis models

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

Abstract Mechanistic models of photosynthesis have expanded substantially over the past decades, covering processes from light reactions to carbon fixation. However, these models remain fragmented across the literature, inconsistently implemented, and difficult to reproduce or reuse, limiting their adoption beyond the research group that developed them. Here, we present GreenSloth, a freely accessible web-based database of 22 published mechanistic photosynthesis models, reimplemented as standardized, executable Python objects within MxlPy, an open-source framework for mechanistic biological modeling. Although the database is primarily designed for dynamic mechanistic models formulated as ordinary differential equations, the current implementation also includes the field’s most widely cited steady-state mechanistic model and its variants. GreenSloth provides a structured environment for model discovery, comparison, and reuse, addressing reproducibility challenges in the field and enabling integration into emerging hybrid modeling approaches. It is also interactive: each model runs directly in the browser, with no installation, environment setup, or programming required. The resource is openly accessible and designed for long-term community maintenance, hoping to position itself as foundational infrastructure for the photosynthesis modeling community. Database URL https://greensloth.rwth-aachen.de/

Authors 9

1. Elouën Corvest Aachen Computational Life Science Department of Biology

   RWTH Aachen University

   Affiliation as printed

   Computational Life Science, Department of Biology, RWTH Aachen University, Germany

2. Marvin van Aalst Aachen Computational Life Science Department of Biology

   RWTH Aachen University

   Affiliation as printed

   Computational Life Science, Department of Biology, RWTH Aachen University, Germany

3. Tim Nies Aachen Computational Life Science Department of Biology

   RWTH Aachen University

   Affiliation as printed

   Computational Life Science, Department of Biology, RWTH Aachen University, Germany

4. Quang Huy Nguyen Aachen Computational Life Science Department of Biology

   Cluster of Excellence on Plant Sciences · Heinrich Heine University Düsseldorf · RWTH Aachen University

   Affiliation as printed

   Cluster of Excellence on Plant Sciences, Heinrich-Heine University Düsseldorf, Germany

   Computational Life Science, Department of Biology, RWTH Aachen University, Germany

5. Josha Ebeling Aachen Computational Life Science Department of Biology

   RWTH Aachen University

   Affiliation as printed

   Computational Life Science, Department of Biology, RWTH Aachen University, Germany

6. Maja Strauch Aachen Computational Life Science Department of Biology

   RWTH Aachen University

   Affiliation as printed

   Computational Life Science, Department of Biology, RWTH Aachen University, Germany

7. El-Hadji Malick Cisse Aachen Computational Life Science Department of Biology

   RWTH Aachen University

   Affiliation as printed

   Computational Life Science, Department of Biology, RWTH Aachen University, Germany

8. Tanvir Hassan Aachen Computational Life Science Department of Biology

   RWTH Aachen University

   Affiliation as printed

   Computational Life Science, Department of Biology, RWTH Aachen University, Germany

9. Anna Matuszyńska corresponding Aachen Center for Computational Life Sciences Computational Life Science Department of Biology

   Cluster of Excellence on Plant Sciences · Heinrich Heine University Düsseldorf · RWTH Aachen University

   Affiliation as printed

   Center for Computational Life Sciences, RWTH Aachen University, Germany

   Cluster of Excellence on Plant Sciences, Heinrich-Heine University Düsseldorf, Germany

   Computational Life Science, Department of Biology, RWTH Aachen University, Germany