Mapping the knowledge landscape of planarian regeneration: a century of bibliometric insights

Despite over two centuries of research, the knowledge landscape of planarian regeneration-a pivotal model for stem cell biology and regenerative medicine-remains fragmented, hindering interdisciplinary integration and translational progress. To address this gap, we conducted the first large-scale bibliometric analysis integrating machine learning-enhanced burst detection, hierarchical clustering analysis, and cross-disciplinary network mapping.

We systematically analyzed 1,685 publications (1900-2025) from the Web of Science Core Collection, constructing a high-resolution knowledge map that reveals the field's dynamic evolution. Our analysis identifies three distinct phases: initial morphological exploration (1900-2010), molecular mechanism elucidation (2011-2020), and the current era of interdisciplinary convergence (2021-2025). The United States leads in output and global collaboration, while China ranks third but exhibits limited international engagement. Burst detection highlights emerging frontiers in stem cell regulation, environmental toxicology, and computational modeling. Hierarchical clustering and discipline overlay mapping further uncover convergence between developmental biology and environmental science, neuroscience, education, and engineering. By constructing a high-resolution knowledge map, we identify underexplored thematic intersections suggested by publication trends, thereby providing a data-driven roadmap to navigate future research priorities.

This work provides a structured synthesis of planarian regeneration research, offering a data-driven roadmap to inform future studies, while illustrating how bibliometric approaches can complement traditional literature reviews.