标题： 生物相关化学空间的加权网络分析 显示英文标题

标题： Weighted Network Analysis of Biologically Relevant Chemical Spaces

摘要： 在化学生物信息学中，化合物空间的网络表示已被广泛提出。 其中，阈值网络由代表分子的节点组成。 在此网络表示中，如果两个分子之间的Tanimoto系数（一种相似性度量）超过预设阈值，则它们通过链接相连。 然而，阈值网络的拓扑结构会受到预设阈值的显著影响。 在本研究中，我们收集了生物相关化合物和生物活性的数据。 我们定义了加权网络，其中每个节点之间的链接权重等于生物活性化合物（节点）之间的Tanimoto系数，而无需使用阈值。 我们研究了加权网络中链接强度与生物活性接近性之间的关系。 我们发现，具有显著高或低生物活性的化合物比整体网络中的化合物有更强的连接。 显示英文摘要

摘要： In cheminformatics, network representations of the space of compounds have been suggested extensively. Among these, the threshold-network consists of nodes representing molecules. In this network representation, two molecules are connected by a link if the Tanimoto coefficient, a similarity measure, between them exceeds a preset threshold. However, the topology of the threshold-network is affected significantly by the preset threshold. In this study, we collected the data of biologically relevant compounds and bioactivities. We defined the weighted network where the weight of each link between the nodes equals the Tanimoto coefficient between the bioactive compounds (nodes) without using the threshold. We investigated the relationship between the strength of the link connection and the bioactivity closeness in the weighted networks. We found that compounds with significantly high or low bioactivity have a stronger connection than those in the overall network.