Metabolic pathway is an important type of biological pathways. It produces essential molecules and energies to maintain the life of living organisms. Each metabolic pathway consists of a chain of chemical reactions, which always need enzymes to participate in. Thus, chemicals and enzymes are two major components for each metabolic pathway. Although several metabolic pathways have been uncovered, the metabolic pathway system is still far from complete. Some hidden chemicals or enzymes are not discovered in a certain metabolic pathway. Besides the traditional experiments to detect hidden chemicals or enzymes, an alternative pipeline is to design efficient computational methods. In this study, we proposed a powerful multilabel classifier, called iMPTCE-Hnetwork, to uniformly assign chemicals and enzymes to metabolic pathway types reported in KEGG. Such classifier adopted the embedding features derived from a heterogeneous network, which defined chemicals and enzymes as nodes and the interactions between chemicals and enzymes as edges, through a powerful network embedding algorithm, Mashup. The popular RAndom k-labELsets (RAKEL) algorithm was employed to construct the classifier, which incorporated the support vector machine (polynomial kernel) as the basic classifier. The ten-fold cross-validation results indicated that such a classifier had good performance with accuracy higher than 0.800 and exact match higher than 0.750. Several comparisons were done to indicate the superiority of the iMPTCE-Hnetwork.

中文翻译：

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iMPTCE-Hnetwork：一种多标签分类器，用于识别具有异构网络的化学物质和酶的代谢途径类型

代谢途径是一类重要的生物途径。它产生必要的分子和能量来维持生物体的生命。每条代谢途径都由一系列化学反应组成，这些反应总是需要酶参与。因此，化学物质和酶是每条代谢途径的两个主要组成部分。尽管已经发现了几种代谢途径，但代谢途径系统还远未完成。某些隐藏的化学物质或酶在某些代谢途径中未被发现。除了检测隐藏化学物质或酶的传统实验外，另一种方法是设计有效的计算方法。在这项研究中，我们提出了一个强大的多标签分类器，称为 iMPTCE-Hnetwork，将化学物质和酶统一分配给 KEGG 中报告的代谢途径类型。这种分类器采用了来自异构网络的嵌入特征，通过强大的网络嵌入算法 Mashup，将化学品和酶定义为节点，将化学品和酶之间的相互作用定义为边。使用流行的 RANdom k-labELsets (RAKEL) 算法来构建分类器，其中包含支持向量机（多项式核）作为基本分类器。十倍交叉验证结果表明，这种分类器具有良好的性能，准确度高于0.800，精确匹配高于0.750。进行了几次比较以表明 iMPTCE-H 网络的优越性。通过强大的网络嵌入算法 Mashup。使用流行的 RANdom k-labELsets (RAKEL) 算法来构建分类器，其中包含支持向量机（多项式核）作为基本分类器。十倍交叉验证结果表明，这种分类器具有良好的性能，准确度高于0.800，精确匹配高于0.750。进行了几次比较以表明 iMPTCE-H 网络的优越性。通过强大的网络嵌入算法 Mashup。使用流行的 RANdom k-labELsets (RAKEL) 算法来构建分类器，其中包含支持向量机（多项式核）作为基本分类器。十倍交叉验证结果表明，这种分类器具有良好的性能，准确度高于0.800，精确匹配高于0.750。进行了几次比较以表明 iMPTCE-H 网络的优越性。800 和精确匹配高于 0.750。进行了几次比较以表明 iMPTCE-H 网络的优越性。800 和精确匹配高于 0.750。进行了几次比较以表明 iMPTCE-H 网络的优越性。