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 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.
Authors
- George A. Soultoukis (ORCID: https://orcid.org/0000-0002-7290-1444)
- Marina Leer
- Dirk Walther (ORCID: https://orcid.org/0000-0002-5755-9265)
- Markus Jähnert (ORCID: https://orcid.org/0000-0001-6459-7318)
- Tim Julius Schulz (ORCID: https://orcid.org/0000-0002-8413-3972)
- Masoome Oveisi
Institutions
- University of Potsdam (DE)
- Max Planck Institute of Molecular Plant Physiology (DE)
- Deutsches Diabetes-Zentrum e.V. (DE)
- German Center for Diabetes Research (DE)
- German Institute of Human Nutrition (DE)
- Heinrich Heine University Düsseldorf (DE)
Publication Details
- Journal
- Frontiers in Bioinformatics
- Published
- 2025-05-06
- DOI
- https://doi.org/10.3389/fbinf.2025.1523184
- Citations
- 1
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.81