@article {3165544,
	title = {GENI: A web server to identify gene set enrichments in tumor samples},
	journal = {Comput Struct Biotechnol J},
	volume = {21},
	year = {2023},
	month = {2023},
	pages = {5531-5537},
	abstract = {<p>
	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, https://www.shaullab.com/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{\textquoteright}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.
</p>
},
	issn = {2001-0370},
	doi = {10.1016/j.csbj.2023.10.053},
	author = {Hayashi, Arata and Ruppo, Shmuel and Heilbrun, Elisheva E and Mazzoni, Chiara and Adar, Sheera and Yassour, Moran and Rmaileh, Areej Abu and Shaul, Yoav D}
}
