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Predictive modeling of gene expression regulation
2021
BMC Bioinformatics
Background In-depth analysis of regulation networks of genes aberrantly expressed in cancer is essential for better understanding tumors and identifying key genes that could be therapeutically targeted. Results We developed a quantitative analysis approach to investigate the main biological relationships among different regulatory elements and target genes; we applied it to Ovarian Serous Cystadenocarcinoma and 177 target genes belonging to three main pathways (DNA REPAIR, STEM CELLS and
doi:10.1186/s12859-021-04481-1
pmid:34837938
pmcid:PMC8626902
fatcat:6nlib55efrf4zkvy4tp4efk5au