精准医疗的网络建模方法
Network modeling methods for precision medicine
摘要：
我们在本次调查中讨论了几种网络建模方法及其对精准医学的适用性。我们回顾了几种网络中心性方法（度中心性，接近中心性，偏心中心性，介数中心性和基于特征向量的声望）和两种系统可控性方法（最小控制集和网络结构可控性）。我们在三个多发性骨髓瘤患者疾病网络上证明了它们对精准医学的适用性。每个网络都由围绕特定患者的突变基因、围绕多发性骨髓瘤标准治疗中使用的药物靶标以及围绕多发性骨髓瘤特异性必需基因构建的蛋白质相互作用组成。对于每个网络，我们展示了我们讨论的网络方法如何用于识别独特适合该患者的个性化靶向药物组合。
英文摘要：
We discuss in this survey several network modeling methods and their applicability to precision medicine. We review several network centrality methods (degree centrality, closeness centrality, eccentricity centrality, betweenness centrality, and eigenvector-based prestige) and two systems controllability methods (minimum dominating sets and network structural controllability). We demonstrate their applicability to precision medicine on three multiple myeloma patient disease networks. Each network consists of protein-protein interactions built around a specific patient's mutated genes, around the targets of the drugs used in the standard of care in multiple myeloma, and around multiple myeloma-specific essential genes. For each network we demonstrate how the network methods we discuss can be used to identify personalized, targeted drug combinations uniquely suited to that patient.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
