Prediction and Analysis of Key Genes in Glioblastoma Based on Bioinformatics

Abstract

Understanding the mechanisms of glioblastoma at the molecular and structural level is not only interesting for basic science but also valuable for biotechnological application, such as the clinical treatment. In the present study, bioinformatics analysis was performed to reveal and identify the key genes of glioblastoma multiforme (GBM). The results obtained in the present study signified the importance of some genes, such as COL3A1, FN1, and MMP9, for glioblastoma. Based on the selected genes, a prediction model was built, which achieved 94.4% prediction accuracy. These findings might provide more insights into the genetic basis of glioblastoma.