A Query-to-Dashboard Framework for Reproducible PubMed-Scale Bibliometrics and Trend Intelligence

Abstract

The rapid expansion of biomedical literature necessitates computational approaches for systematic analysis of publication patterns, identification of emerging scientific themes, and characterization of field evolution. We present PubMed Atlas, an integrated command-line and web-based platform for conducting topic-specific bibliometric analyses through programmatic access to PubMed E-utilities. This workflow retrieves PubMed identifiers matching user-defined queries, downloads comprehensive metadata in batch mode, extracts structured information including titles, abstracts, author affiliations, Medical Subject Headings, publication classifications, funding acknowledgments, and digital object identifiers, then organizes these data within a local SQLite relational database optimized for rapid queries and visualization. An accompanying Streamlit-based interactive dashboard enables exploration of temporal publication patterns, journal distribution profiles, MeSH term frequencies, geographic author distributions, and direct linking to recent publications. We demonstrate the application of PubMed Atlas to cancer stem cell biology and stem cell transcriptional regulatory network research, providing a framework for reproducible bibliometric investigation and systematic identification of research gaps within dynamically evolving scientific domains.