Communications Biology (Apr 2024)

Rummagene: massive mining of gene sets from supporting materials of biomedical research publications

  • Daniel J. B. Clarke,
  • Giacomo B. Marino,
  • Eden Z. Deng,
  • Zhuorui Xie,
  • John Erol Evangelista,
  • Avi Ma’ayan

DOI
https://doi.org/10.1038/s42003-024-06177-7
Journal volume & issue
Vol. 7, no. 1
pp. 1 – 13

Abstract

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Abstract Many biomedical research publications contain gene sets in their supporting tables, and these sets are currently not available for search and reuse. By crawling PubMed Central, the Rummagene server provides access to hundreds of thousands of such mammalian gene sets. So far, we scanned 5,448,589 articles to find 121,237 articles that contain 642,389 gene sets. These sets are served for enrichment analysis, free text, and table title search. Investigating statistical patterns within the Rummagene database, we demonstrate that Rummagene can be used for transcription factor and kinase enrichment analyses, and for gene function predictions. By combining gene set similarity with abstract similarity, Rummagene can find surprising relationships between biological processes, concepts, and named entities. Overall, Rummagene brings to surface the ability to search a massive collection of published biomedical datasets that are currently buried and inaccessible. The Rummagene web application is available at https://rummagene.com .