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靶标识别是现代药物研发中的重要一环,针对具体疾病的靶标识别已经成为疾病新药研发的最重要问题。本文依照网络药理学的思想,采用复杂网络分析方法,构建了人类蛋白质反应网络和表型相似度网络,结合已知心脑血管相关靶标蛋白质,训练得到网络节点分类器,并以此预测新的潜在靶标。同以往的靶标发现方法相比,本文从一个新的角度对靶标识别问题重新建模求解。本文所提出的方法能够有效的预测心脑血管疾病潜在靶标基因,为新药研发提供有力的支撑。
Target recognition is an important part of modern drug development. Target-specific target recognition has become the most important issue for the development of new drugs for diseases. In this paper, according to the idea of network pharmacology, a complex network analysis method is used to construct a human protein response network and a network of phenotypic similarity. By combining known cardiovascular and cerebrovascular related target proteins, a network node classifier is trained to predict new Potential target. Compared with the previous methods of target discovery, this paper reconstructs the target recognition problem from a new perspective. The proposed method can effectively predict potential target genes of cardiovascular and cerebrovascular diseases and provide strong support for the development of new drugs.