Development of a susceptibility gene based novel predictive model for the diagnosis of ulcerative colitis using random forest and artificial neural network.
Development of a susceptibility gene based novel predictive model for the diagnosis of ulcerative colitis using random forest and artificial neural network.
复制标题
使用随机森林和人工神经网络开发基于易感基因的新型预测模型，用于诊断溃疡性结肠炎。
DOI：
10.18632/aging.103861
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发表时间：
2020-10-24
期刊：
影响因子：
--
通讯作者：
Shen J
中科院分区：
文献类型：
--
作者：
Li H;Lai L;Shen J
溃疡性结肠炎是一种炎症性肠病，其特征是肠道慢性和复发性非特异性炎症。为了寻找易感基因并开发溃疡性结肠炎的新型预测模型，下载了包含溃疡性结肠炎基因表达谱（训练集GSE109142和验证集GSE92415）的两组病例和对照组，并用于识别差异表达基因。 GSE109142中总共鉴定出781个上调和127个下调的差异表达基因。引入随机森林算法来确定对溃疡性结肠炎发生影响最大的 1 个下调和 29 个上调差异表达基因。将这30个基因的表达数据转化为基因表达评分，并开发人工神经网络模型来计算溃疡性结肠炎差异表达基因的权重。我们根据30个基因的表达数据建立了通用分子预后评分（mPS），并用GSE92415验证了mPS系统。预测结果与独立数据集一致（ROC-AUC=0.9506/PR-AUC=0.9747）。我们的研究为溃疡性结肠炎的诊断创建了可靠的预测模型，并为疾病早期筛查的进一步研究提供了替代标记物组
Ulcerative colitis is a type of inflammatory bowel disease characterized by chronic and recurrent nonspecific inflammation of the intestinal tract. To find susceptibility genes and develop a novel predictive model of ulcerative colitis, two sets of cases and a control group containing the ulcerative colitis gene expression profile (training set GSE109142 and validation set GSE92415) were downloaded and used to identify differentially expressed genes. A total of 781 upregulated and 127 downregulated differentially expressed genes were identified in GSE109142. The random forest algorithm was introduced to determine 1 downregulated and 29 upregulated differentially expressed genes contributing highest to ulcerative colitis occurrence. Expression data of these 30 genes were transformed into gene expression scores, and an artificial neural network model was developed to calculate differentially expressed genes weights to ulcerative colitis. We established a universal molecular prognostic score (mPS) based on the expression data of the 30 genes and verified the mPS system with GSE92415. Prediction results agreed with that of an independent data set (ROC-AUC=0.9506/PR-AUC=0.9747). Our research creates a reliable predictive model for the diagnosis of ulcerative colitis, and provides an alternative marker panel for further research in disease early screening
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DOI：
10.1016/j.cgh.2017.06.016
发表时间：
2018-03
期刊：
Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
影响因子：
--
作者：
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影响因子：
3.1
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DOI：
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发表时间：
2017-04
期刊：
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影响因子：
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影响因子：
15.9
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