pubCounteR: an R package for interrogating published literature for experimentally-derived gene lists within a user-defined biological context

Basic and clinical biomedical research relies heavily on modern large-scale datasets that include genomics, transcriptomics, epigenomics, metabolomics, and proteomics, among other “Omics”. These research tools very often generate lists of candidate genes that are hypothesized or shown to be responsi...

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Bibliographic Details
Main Authors: Marina Leer, George A. Soultoukis, Markus Jähnert, Masoome Oveisi, Dirk Walther, Tim J. Schulz
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-05-01
Series:Frontiers in Bioinformatics
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Online Access:https://www.frontiersin.org/articles/10.3389/fbinf.2025.1523184/full
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Summary:Basic and clinical biomedical research relies heavily on modern large-scale datasets that include genomics, transcriptomics, epigenomics, metabolomics, and proteomics, among other “Omics”. These research tools very often generate lists of candidate genes that are hypothesized or shown to be responsible for the biological effect in question. To aid the biological interpretation of experimentally-obtained gene lists, we developed pubCounteR, an R-package and web-based interface that screens publications by a user-defined set of keywords representing a specific biological context for experimentally-derived gene lists.
ISSN:2673-7647