Identify Inflammatory Bowel Disease-Related Genes Based on Machine Learning.
Identify Inflammatory Bowel Disease-Related Genes Based on Machine Learning.
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DOI：
10.3389/fcell.2021.722410
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发表时间：
2021
影响因子：
5.5
通讯作者：
Cui C
中科院分区：
文献类型：
--
作者：
Ye L;Lin Y;Fan XD;Chen Y;Deng Z;Yang Q;Lei X;Mao J;Cui C
炎症性肠病（IBD）患者在全球范围内不断增加。IBD具有反复发作、难以治愈的特点，也是结直肠癌（CRC）的高危因素之一。IBD的发生与遗传因素密切相关，这促使我们寻找IBD相关基因。基于相似疾病与相似基因相关的假设，提出了一种基于支持向量机的IBD相关基因识别方法。共获得135种与IBD相似的疾病及其相关基因。这些基因被认为是IBD相关基因的候选者。我们提取每个基因的特征，并实施SVM来识别它与IBD相关的概率。十交叉验证，以验证我们的方法的有效性。AUC为0.93，AUPR为0.97，是四种方法中最好的。我们对候选基因进行了优先排序，并对前五个基因进行了案例研究。
The patients of Inflammatory bowel disease (IBD) are increasing worldwide. IBD has the characteristics of recurring and difficult to cure, and it is also one of the high-risk factors for colorectal cancer (CRC). The occurrence of IBD is closely related to genetic factors, which prompted us to identify IBD-related genes. Based on the hypothesis that similar diseases are related to similar genes, we purposed a SVM-based method to identify IBD-related genes by disease similarities and gene interactions. One hundred thirty-five diseases which have similarities with IBD and their related genes were obtained. These genes are considered as the candidates of IBD-related genes. We extracted features of each gene and implemented SVM to identify the probability that it is related to IBD. Ten-cross validation was applied to verify the effectiveness of our method. The AUC is 0.93 and AUPR is 0.97, which are the best among four methods. We prioritized the candidate genes and did case studies on top five genes.
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