The project involves applying bioinformatics and machine learning methods to analyze uterine endometrial cancer data, aiming to identify key genes associated with the disease and further investigating their potential roles.
To achieve this, data will be sourced from public databases like GEO and TCGA. The analysis process, including identifying differentially expressed genes, functional enrichment analysis, machine learning for key gene identification, and other bioinformatics techniques, should follow a structure and methodology similar to the article I attached earlier. From the analysis to writing the article, excluding the experimental section in the reference article, everything else will be completed by you.
Bioinformatics Analysis
FromPeoplePerHour
