GENI: A web server to identify gene set enrichments in tumor samples

Arata Hayashi, Shmuel Ruppo, Elisheva E. Heilbrun, Chiara Mazzoni, Sheera Adar, Moran Yassour, Areej Abu Rmaileh, Yoav D. Shaul*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The Cancer Genome Atlas (TCGA) and analogous projects have yielded invaluable tumor-associated genomic data. Despite several web-based platforms designed to enhance accessibility, certain analyses require prior bioinformatic expertise. To address this need, we developed Gene ENrichment Identifier (GENI,, which is designed to promptly compute correlations for genes of interest against the entire transcriptome and rank them against well-established biological gene sets. Additionally, it generates comprehensive tables containing genes of interest and their corresponding correlation coefficients, presented in publication-quality graphs. Furthermore, GENI has the capability to analyze multiple genes simultaneously within a given gene set, elucidating their significance within a specific biological context. Overall, GENI's user-friendly interface simplifies the biological interpretation and analysis of cancer patient-associated data, advancing the understanding of cancer biology and accelerating scientific discoveries.

Original languageAmerican English
Pages (from-to)5531-5537
Number of pages7
JournalComputational and Structural Biotechnology Journal
StatePublished - Jan 2023

Bibliographical note

Publisher Copyright:
© 2023 The Authors


  • Bioinformatics
  • Cancer biology
  • Cancer-associated molecular mechanisms
  • Clinical data
  • Gene Set Enrichment Analysis
  • Multi-Gene Analysis
  • TCGA
  • Tumor samples
  • Web-based tools


Dive into the research topics of 'GENI: A web server to identify gene set enrichments in tumor samples'. Together they form a unique fingerprint.

Cite this