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Rxiv-Maker converts Markdown to publication-ready PDFs via automated LaTeX processing, enabling reproducible workflows without requiring LaTeX expertise. The system runs Python and R scripts at compilation to generate synchronized figures from data, with citations and cross-references handled automatically. 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Saraiva 1,􀀀, Guillaume Jaquemet2,3,4,􀀀, and Ricardo Henriques 1,5,􀀀  \n1 Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal  \n2 Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku, Finland  \n3 InFLAMES Research Flagship Center, University of Turku, Turku, Finland  \n4Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland  \n5 UCL Laboratory for Molecular Cell Biology, University College London, London, United Kingdom  \narXiv :2508 .00836v3 [ cs .DL] 13 Aug 2025  \nPreprint servers have become central to research communication, but authors still struggle with manuscript preparation and typesetting. Rxiv-Maker converts Markdown documents to publication-ready PDFs through automated LaTeX processing. Researchers can focus on content while the system handles formatting and typesetting without requiring LaTeX knowledge. The tool supports version control and collaborative editing workflows common in modern research teams. Python and R scripts execute during compilation to generate figures directly from data, keeping visualisations synchronised with analyses. Docker containerisation and automated build systems provide consistent results across different computing environments. Mathematical notation, citations, and cross-references are processed automatically during conversion. This manuscript was prepared using Rxiv-Maker.  \narticle template | scientific publishing | preprints  \nCorrespondence: (B. M. Saraiva) [bsaraiva@itqb.unl.pt](bsaraiva@itqb.unl.pt); (G. Jaquemet) guil[laume.jacquemet@abo.fi](laume.jacquemet@abo.fi); (R. Henriques) [ricardo.henriques@itqb.unl.pt](ricardo.henriques@itqb.unl.pt)  \nMain  \nPreprint servers like arXiv, bioRxiv, and medRxiv have become central to research communication (1–3) . As submission rates climb (Fig. S1, Fig. S2), researchers now handle tasks once managed by journal production teams (4, 5) . Most manuscript preparation workflows use proprietary formats that work poorly with version control systems, making collaborative research more difficult (6) .  \nComputational research faces particular challenges because algorithms, analysis methods, and processing pipelines change frequently. In computational biology, researchers struggle to keep manuscripts synchronized with evolving analysis code, leading to publications that don’t accurately describe the methods used.  \nBioimage analysis shows these problems clearly: collaborative frameworks (7) and containerised analysis environments (8) highlight how important reproducible computational workflows are for scientific publishing.  \nRxiv-Maker helps address these challenges by providing a developer-centric framework for reproducible preprint preparation. It generates publication-standard PDFs through automated LaTeX processing and works directly with Git workflows and continuous integration practices. Built-in reproducibility features ensure manuscripts build consistently across different systems and over time.  \nManuscript preparation becomes a transparent process that  \nFig. 1. The Rxiv-Maker System Diagram. The system integrates Markdown content, YAML metadata, Python and R scripts, and bibliography files through a processing engine. This engine leverages GitHub Actions, virtual environments, and LaTeX to produce a publication-ready scientific article, demonstrating a fully automated and reproducible pipeline.  \ngives researchers access to professional typesetting tools. A Visual Studio Code extension provides syntax highlighting and automated citation management. Researchers can leverage familiar development environments while maintaining rigorous version control and reproducibility guarantees. This bridges traditional authoring workflows with contemporary best practices in computational research.  \nThe framework enables programmatic generation of f","cbCaib65Yxbf83FZ","https://ap.wps.com/l/cbCaib65Yxbf83FZ","pdf",692455,12,"English","# Main\n## Challenges in preprint manuscript preparation\n## Reproducible computational workflows\n## Rxiv-Maker workflow and capabilities\n## Executable figures and diagrams\n## Git-based automation and reproducibility","[{\"question\":\"What problem does Rxiv-Maker target in scientific manuscript preparation?\",\"answer\":\"It addresses difficulties in formatting and typesetting for preprints, especially ensuring manuscripts stay synchronized with evolving computational methods and analysis code.\"},{\"question\":\"How does Rxiv-Maker convert manuscripts to publication-ready outputs?\",\"answer\":\"It converts Markdown documents to publication-ready PDFs through automated LaTeX processing, including automatic handling of mathematical notation, citations, and cross-references.\"},{\"question\":\"What makes Rxiv-Maker reproducible across different systems and over time?\",\"answer\":\"It uses Git workflows and automated build practices, including containerisation and consistent compilation setups, so manuscripts build consistently across environments and dataset/code updates.\"}]","Rxiv-Maker - an automated template engine for streamlined scientific publications | PDF"]