基于蛋白质相互作用网络局部相似度的肝癌疾病基因预测

Predicting HCC-causative genes based on local similarity indices in human protein-protein interaction network

基于人类蛋白质相互作用网络,该文采纳拓扑局部相似度去实现肝癌疾病基因的预测.交叉检验测试结果表明:有22%~29%的目标基因在候选基因中排名前5%,且预测精度均能达到0.7以上.归因于低的计算复杂度和相对高的预测精度,这类疾病基因预测方法可为发现和鉴定疾病基因提供有力的线索.

Based on the human protein-protein interaction network,we adopt the local topological similarity in network to predict the hepatocellular-carcinoma(HCC)-related genes.The cross validation showed that the AUC of every similarity index can exceed 0.7,and 22%to 29%known disease genes are at top 5%.Due to both low computing complexity and relatively high prediction accuracy,they might be helpful for disease-related genes discover and identification.