Biomedical systems biology workflow orchestration and execution with PoSyMed

📅 2026-04-21
📈 Citations: 0
Influential: 0
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🤖 AI Summary
This work addresses the pervasive challenges in bioinformatics tooling—such as fragmentation, complex dependencies, inconsistent documentation, and irreproducible environments—that severely hinder method reuse and adaptation. To overcome these limitations, the authors propose PoSyMed, an open modular platform that integrates biomedical workflows through formalized tool descriptions, containerized execution, a persistent workflow engine, and a conversational interface. Innovatively, a large language model is incorporated as a semantic assistant within a typed, validated, and human-supervised framework to support tool discovery, pipeline construction, and parameter configuration. This design significantly enhances analytical transparency and reproducibility. The platform’s efficacy is demonstrated in representative biomedical use cases, and it has been released as open-source software.

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📝 Abstract
The rapid growth of scientific software has created practical barriers for bioinformatics research. Although powerful statistical, artificial intelligence (AI)-based methods are now widely available, their effective use is often hindered by fragmented distribution, inconsistent documentation, complex dependencies, and difficult-to-reproduce execution environments. As a result, reusing published tools and workflow adaptation to own date remains technically demanding and time-intensive, even for experienced users. Here, we present PoSyMed, an open and modular platform for the controlled integration, composition, and execution of bioinformatics tools and workflows. PoSyMed combines a backend-centered platform architecture with formal tool descriptions, controlled container-based build and execution processes, persistent workflow state, and a dialogue-based user interface. Large language models (LLM) are integrated not as autonomous decision-makers, but as human-computer interface with bounded semantic assistants that help identify tools, propose workflow steps, and support parameterization within a typed, validated, and human-supervised execution environment. PoSyMed is designed to improve reproducibility, traceability, and transparency in practical biomedical analysis within one platform. We describe the system architecture and evaluate its behavior across representative biological software scenarios with respect to workflow support, interaction design, and platform extensibility. PoSyMed is publicly available at https://apps.cosy.bio/posymed.
Problem

Research questions and friction points this paper is trying to address.

workflow orchestration
reproducibility
bioinformatics tools
execution environment
software integration
Innovation

Methods, ideas, or system contributions that make the work stand out.

workflow orchestration
container-based execution
large language models
reproducibility
biomedical systems biology
S
Simon Süwer
Institute for Computational Systems Biomedicine, University of Hamburg, Hamburg, Germany
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Zoe Chervontseva
Institute for Computational Systems Biomedicine, University of Hamburg, Hamburg, Germany
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Kester Bagemihl
Institute for Computational Systems Biomedicine, University of Hamburg, Hamburg, Germany
Jan Baumbach
Jan Baumbach
Institute for Computational Systems Biology, University of Hamburg
BioinformaticsComputer ScienceArtifical IntelligenceSystems BiologySystems Medicine
O
Olga Tsoy
Institute for Computational Systems Biomedicine, University of Hamburg, Hamburg, Germany; Faculty of Science, Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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Andreas Maier
Institute for Computational Systems Biomedicine, University of Hamburg, Hamburg, Germany