Prediction and Analysis of Key Genes in Glioblastoma Based on Bioinformatics.
Prediction and Analysis of Key Genes in Glioblastoma Based on Bioinformatics.
复制标题
基于生物信息学的胶质母细胞瘤关键基因预测与分析。
DOI：
10.1155/2017/7653101
复制
发表时间：
2017
影响因子：
--
通讯作者：
Song Y
中科院分区：
文献类型：
--
作者：
Long H;Liang C;Zhang X;Fang L;Wang G;Qi S;Huo H;Song Y
从分子和结构水平了解胶质母细胞瘤的发病机制不仅对基础科学有意义，而且对生物技术的应用（如临床治疗）也有价值。本研究通过生物信息学分析，揭示和鉴定多形性胶质母细胞瘤（GBM）的关键基因。本研究的结果表明，一些基因，如COL3A1，FN 1和MMP 9，胶质母细胞瘤的重要性。根据筛选出的基因建立预测模型，预测准确率达到94.4%。这些发现可能为胶质母细胞瘤的遗传基础提供更多的见解。
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.