CAJ | 학술논문

在构建蛋白质相互作用网络时从通路数据出发，利用通路数据整合蛋白质相互作用网络。提出了一个基于随机游走的蛋白质功能预测方法，在该算法中把已知功能的蛋白质当作起始点，对于随机游走在蛋白质互作网络中产生的邻居信息，转换为注释模式信息，并根据已知功能的蛋白质的功能来提取未知功能蛋白质的注释模式。利用传统的 K近邻算法从训练样本集中找到未知功能蛋白质的k个最近邻。最后，结合多标签分类的K近邻算法，统计 k个近邻中蛋白质的功能类数目，基于最大后验概率预测未知功能蛋白质属于的功能标签类。通过在构建蛋白质互作网络进行实验，结果表明提出的方案能够有效地进行蛋白质功能预测。
재구건단백질상호작용망락시종통로수거출발，이용통로수거정합단백질상호작용망락。제출료일개기우수궤유주적단백질공능예측방법，재해산법중파이지공능적단백질당작기시점，대우수궤유주재단백질호작망락중산생적린거신식，전환위주석모식신식，병근거이지공능적단백질적공능래제취미지공능단백질적주석모식。이용전통적 K근린산법종훈련양본집중조도미지공능단백질적k개최근린。최후，결합다표첨분류적K근린산법，통계 k개근린중단백질적공능류수목，기우최대후험개솔예측미지공능단백질속우적공능표첨류。통과재구건단백질호작망락진행실험，결과표명제출적방안능구유효지진행단백질공능예측。
In the process of constructing the protein-protein interaction network is starting from the pathway data ,data integration using pathway of protein interaction networks . A prediction method for protein function is presented based on random walk ,in this algorithm ,the proteins of known function as a starting point is provided , for the random walk in the protein interaction network of neighborhood information ,annotation schema information is converted ,and according to the known function protein function to extract the unknown function protein annotation mode . After ,using the traditional KNN algorithm to find the unknown function protein the k nearest neighbors from the training set . Last , combined with KNN algorithm for multi label classification ,the maximum posteriori probability prediction function label unknown function protein is based . The experiments in which we construct protein interaction network , the results show that the proposed scheme can predict the protein function effectively .