The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
g:Profiler—a web-based toolset for functional profiling of gene lists from large-scale experiments
Open accessAbstract
g:Profiler (http://biit.cs.ut.ee/gprofiler/) is a public web server for characterising and manipulating gene lists resulting from mining high-throughput genomic data. g:Profiler has a simple, user-friendly web interface with powerful visualisation for capturing Gene Ontology (GO), pathway, or transcription factor binding site enrichments down to individual gene levels. Besides standard multiple testing corrections, a new improved method for estimating the true effect of multiple testing over complex structures like GO has been introduced. Interpreting ranked gene lists is supported from the same interface with very efficient algorithms. Such ordered lists may arise when studying the most significantly affected genes from high-throughput data or genes co-expressed with the query gene. Other important aspects of practical data analysis are supported by modules tightly integrated with g:Profiler. These are: g:Convert for converting between different database identifiers; g:Orth for finding orthologous genes from other species; and g:Sorter for searching a large body of public gene expression data for co-expression. g:Profiler supports 31 different species, and underlying data is updated regularly from sources like the Ensembl database. Bioinformatics communities wishing to integrate with g:Profiler can use alternative simple textual outputs.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
The control of the false discovery rate in multiple testing under dependency
Benjamini, Y., & Yekutieli, D. (2001) · The Annals of Statistics · doi:10.1214/aos/1013699998 · Cited by 10,490
Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197
DAVID: Database for Annotation, Visualization, and Integrated Discovery
Dennis, G., Sherman, B. T., Hosack, D. A., Yang, J., Gao, W., Lane, H. C., & Lempicki, R. A. (2003) · Genome Biology · doi:10.1186/gb-2003-4-5-p3 · Cited by 9,327
Cited by
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn923 · Cited by 14,108
Raudvere, U., Kolberg, L., Kuzmin, I., Arak, T., Adler, P., Peterson, H., & Vilo, J. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz369 · Cited by 5,045
Self-citationA Gene Network Regulating Lysosomal Biogenesis and Function
Sardiello, M., Palmieri, M., di Ronza, A., Medina, D. L., Valenza, M., Gennarino, V. A., Di Malta, C., Donaudy, F., Embrione, V., Polishchuk, R. S., et al. (2009) · Science · doi:10.1126/science.1174447 · Cited by 2,543
Reimand, J., Isserlin, R., Voisin, V., Kucera, M., Tannus-Lopes, C., Rostamianfar, A., Wadi, L., Meyer, M., Wong, J., Xu, C., et al. (2019) · Nature Protocols · doi:10.1038/s41596-018-0103-9 · Cited by 1,970
Self-citationKolberg, L., Raudvere, U., Kuzmin, I., Adler, P., Vilo, J., & Peterson, H. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad347 · Cited by 1,673
Self-citation
Metadata
- Authors
- Reimand, J., Kull, M., Peterson, H., Hansen, J., & Vilo, J.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-07
- Volume
- 35
- Issue
- suppl_2
- Pages
- W193-W200
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2124954099
- Cited by
- 1,545
- References
- 5
- FWCI
- 10.90
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: g:Profiler—a web-based toolset for functional profiling of gene lists from large-scale experiments. https://app.cochat.ai/papers/10.1093/nar/gkm226
- The paper
- Reimand, J., Kull, M., Peterson, H., Hansen, J., & Vilo, J. (2007). g:Profiler—a web-based toolset for functional profiling of gene lists from large-scale experiments. Nucleic Acids Research. https://doi.org/10.1093/nar/gkm226
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
