Pharmacological assessment of <i>Coffea arabica</i> compounds as potential therapeutics for cervical cancer

The data supporting the findings of this study, including bulk RNA-seq gene expression data, survival, and phenotype data, are available through the TCGA database. These data can be accessed via the Xenabrowser platform (https://xenabrowser.net) using the reference identifier [TCGA Cervical Cancer (CESC)]. Corresponding healthy cervical tissue RNA-seq data, are available through the Genotype-Tissue Expression (GTEx) project (https://www.gtexportal.org/home/). The codes used for differential gene expression (DGE) analysis, pathway enrichment, and survival analysis, as well as scripts for generating volcano plots (DGE analysis), Kaplan-Meier survival plots, and boxplots (gene expression), and machine learning implementations are available on GitHub (https://github.com/Ponaskillzyy/Coffea_arabica_Potential_in_Cervical_Cancer).

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Publication Details

Journal
Bioinformatics Advances
Published
2024-12-26
DOI
https://doi.org/10.1093/bioadv/vbaf132
Citations
3
Primary Topic
Antioxidant Activity and Oxidative Stress
Type
article
Field-Weighted Citation Impact
0.67
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article

Pharmacological assessment of Coffea arabica compounds as potential therapeutics for cervical cancer

Victor Omoboyede, John Oluwagbenga Balogun, Haruna Isiyaku Umar, Prosper Obed Chukwuemeka et al.
3 citations
Bioinformatics Advances
Antioxidant Activity and Oxidative Stress
0.67
article

Pharmacological assessment of Coffea arabica compounds as potential therapeutics for cervical cancer

Victor Omoboyede, John Oluwagbenga Balogun, Haruna Isiyaku Umar, Prosper Obed Chukwuemeka, Christopher Busayo Olowosoke, Daniel Okpaise, Nwachukwu Christiana Okonkwo, Onyekachi Victor Onyedikachi, Rita Ononiwu, Sarah Olanrewaju Oladejo
article en
3 citations

Abstract

The data supporting the findings of this study, including bulk RNA-seq gene expression data, survival, and phenotype data, are available through the TCGA database. These data can be accessed via the Xenabrowser platform (https://xenabrowser.net) using the reference identifier [TCGA Cervical Cancer (CESC)]. Corresponding healthy cervical tissue RNA-seq data, are available through the Genotype-Tissue Expression (GTEx) project (https://www.gtexportal.org/home/). The codes used for differential gene expression (DGE) analysis, pathway enrichment, and survival analysis, as well as scripts for generating volcano plots (DGE analysis), Kaplan-Meier survival plots, and boxplots (gene expression), and machine learning implementations are available on GitHub (https://github.com/Ponaskillzyy/Coffea_arabica_Potential_in_Cervical_Cancer).

Bioinformatics AdvancesVol. 5(1)
Lagos State University (NG), Bells University of Technology (NG), Federal University of Technology (NG), University of Ibadan (NG), Nnamdi Azikiwe University (NG), Ondo State Primary Health Care Development Board (NG), Lead City University (NG), Michael Okpara University of Agriculture (NG)
Good health and well-being
Openalex Percentile: Top 35%
Antioxidant Activity and Oxidative Stress
0.67
DOIOpen Access PDFOpenAlex
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