面对海量的生物医学数据，多方位和系统地揭示复杂疾病的发生发展机制、开展新的药物研发成为人们关注的焦点。本项目基于图理论这一强有力工具，针对生物信息学中的几个重要问题，如：生物分子网络的图理论基础、基于全局观点的生物差异网络分析模型与算法、基于图模型和算法的脑疾病研究、药物靶点及增效组合药物预测等，展开研究。项目既重视实际问题驱动的基础理论与算法研究，也重视基础理论在生物信息学中的应用。.本项目通过收集整合相关多类型数据，构建图理论模型和设计算法，将深入刻画生物分子网络的拓扑性质，建立生物差异网络分析方法，并针对具体复杂疾病，预测相关生物分子标记物、新的药物靶点和增效药物组合，进行生物医学验证，开发相应的数据库和应用软件，并推广应用于实际。本项目将对揭示复杂疾病的发生发展机制、发现生物分子标记物、开展新的药物设计等提供重要的理论基础和应用支撑，同时也促进图理论和算法基础的研究。

Under the background of large amount of raw data in the field of biomedical sciences, revealing the development mechanism of complex diseases and developing new drugs in an all-round and systematic manner become the focus of the world. Based on graph theory---a powerful tool, this project mainly focuses on such important problems in the field of bioinformatics as graph theoretical basis of bimolecular network, differential network analysis model and algorithm in a global view, brain diseases research based on graph model and algorithm, prediction for drug-target interactions and synergistic drug combinations. It not only pays attention to basical theory and algorithms driven by actual problems, but also emphasizes their applications in bioinformatics. . By collecting and integrating multi data on biomedicine and constructing graph models and algorithms, this project will characterize topological properties of bimolecular network, set up the analytical method of differential network, predict the related biomarkers, new drug targets and synergistic drug combinations, validate the theoretical result by experiments and design the software on so as to apply to the reality. Both in theoretical and applicable significance, this project will support revealing the mechanism of complex diseases, finding biomarker and designing new drugs, at the same time, promoting the research on graph theory and algorithms.