Topic-Driven Bibliometrics and Trend Intelligence for Stem Cell and Cancer Research.
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摘要
The rapid growth of biomedical literature has created an urgent need for computational tools that enable researchers to systematically analyze publication trends, identify emerging research themes, and map the evolution of scientific fields. PubMed Atlas is a command-line and web-enabled workflow for topic-driven bibliometrics and trend intelligence using PubMed E-utilities. The pipeline executes PubMed queries, retrieves matching PMIDs, downloads full metadata records in batches, parses structured information (title, abstract, authors/affiliations, MeSH terms, publication types, grants, keywords, DOI), and stores normalized data in a local SQLite database for rapid querying and visualization. A Streamlit dashboard provides interactive exploration of publication trends, journal distributions, MeSH term summaries, geographic distributions, and recent article browsing with direct PubMed links. This protocol describes the installation, configuration, and operation of PubMed Atlas for cancer stem cell and stem cell transcriptional network research, and other fields, enabling investigators to conduct reproducible bibliometric analyses and identify knowledge gaps in rapidly evolving fields.
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已索引段落
搜索结果指向这些检索单元，同时保留与出版物的关联。