ArticleNucleic acids research2025
CORESH: a gene signature-based search engine for public gene expression datasets.
Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Transcriptome signatures for the identification of bevacizumab responders in ovarian cancer.Genome medicine · 2026Article
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Authors and funding
8 authors.
Funding
Abstract
Public data repositories like Gene Expression Omnibus (GEO) contain an extensive amount of data from hundreds of thousands of experiments, making them a valuable resource for researchers. A common scenario for utilizing this resource is to show transcriptional similarity of one's own data to a public dataset as evidence of potentially similar biology. However, when searching for such datasets, researchers are usually limited to keyword-based search, which requires having a specific hypothesis and relies on the presence of high-quality metadata in public datasets. Here, we introduce CORESH, a web server designed to systematically find GEO datasets that match a user-provided gene signature-such as a list of top upregulated genes in response to a treatment-in a data-driven manner. CORESH operates on a compendium of >40 000 human and 40 000 mouse datasets and outputs a ranked list of datasets where the input genes exhibit similar expression patterns. The discovered datasets can then be used to identify experimental conditions associated with the activation of the query signature, offering insights into underlying biological mechanisms and guiding experimental validation. CORESH is freely accessible at https://alserglab.wustl.edu/coresh/, requires no login, and is regularly updated with the latest GEO data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.