The work presented in this paper is essentially to model real systems in Traditional Chinese Medicine (TCM) using complex networks and to propose different network-based approaches, in order to solve practical problems in TCM research. In the research of TCM formula, we proposed an approach employing molecular networks to predict the effective components of a TCM formula and then uncover its mode of action. In the research of syndrome, we used symptom network to study the clinical rules of different syndromes in same disease, and built a decision support system for TCM diagnosis and treatment based on multilevel association networks. More specifically, the work of this paper involves several aspects as introduced below. (1). Uncovering the mode of action of a TCM formula. Due to the high cost and long period of high-throughput assays, we proposed an approach to uncover the mode of action of a TCM formula based on its molecular network. First, according to the herbal composition of a TCM formula, all chemical components in each herb were collected and the potential targets associated with these chemicals were also retrieved from pharmacological databases. The interactions between potential targets were subsequently extracted from PPI (protein-protein interaction) databases. A gene network for the formula could be constructed. Second, Girvan-Newman algorithm was employed to detect modules from the gene network, and key modules were studied through enrichment analysis. Third, we computed the association scores between chemicals and enriched pathways via common genes and interactions. The association scores between diseases and pathways were computed in a similar way. Fourth, we predicted effective components of the formula by combining chemical-pathway and disease-pathway associations, and investigated the molecular mechanism through enriched pathways related to effective components. Finally, this approach was used to predict effective drugs for Parkinson's disease, and then uncover the mode of action of Shufeng jiedu capsule (an anti-influenza formula). The results of both experiments demonstrated that this approach is accurate and effective to uncover the molecular mechanism of TCM formulae. (2). A module detection algorithm based on mixed modularity. Based on the idea of “chemicals with similar structures have similar properties”, we introduced chemical similarity to the molecular system of a TCM formula. Thus, the molecular system could be model...
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