Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, USA.
J Neurotrauma. 2013 Jul 1;30(13):1101-16. doi: 10.1089/neu.2012.2631.
The rate of traumatic brain injury (TBI) in service members with wartime injuries has risen rapidly in recent years, and complex, variable links have emerged between TBI and long-term neurological disorders. The multifactorial nature of TBI secondary cellular response has confounded attempts to find cellular biomarkers for its diagnosis and prognosis or for guiding therapy for brain injury. One possibility is to apply emerging systems biology strategies to holistically probe and analyze the complex interweaving molecular pathways and networks that mediate the secondary cellular response through computational models that integrate these diverse data sets. Here, we review available systems biology strategies, databases, and tools. In addition, we describe opportunities for applying this methodology to existing TBI data sets to identify new biomarker candidates and gain insights about the underlying molecular mechanisms of TBI response. As an exemplar, we apply network and pathway analysis to a manually compiled list of 32 protein biomarker candidates from the literature, recover known TBI-related mechanisms, and generate hypothetical new biomarker candidates.
近年来，有战争创伤的军人中创伤性脑损伤（TBI）的发生率迅速上升，TBI 与长期神经障碍之间出现了复杂的、多变的联系。TBI 继发细胞反应的多因素性质使得寻找用于其诊断和预后的细胞生物标志物或用于指导脑损伤治疗的生物标志物变得复杂。一种可能性是应用新兴的系统生物学策略，通过整合这些不同数据集的计算模型，全面探测和分析介导继发细胞反应的复杂交织分子途径和网络。在这里，我们回顾了现有的系统生物学策略、数据库和工具。此外，我们还描述了将这种方法应用于现有的 TBI 数据集的机会，以识别新的生物标志物候选者，并深入了解 TBI 反应的潜在分子机制。作为一个范例，我们应用网络和途径分析对文献中手动编制的 32 个蛋白质生物标志物候选者列表进行分析，恢复已知的 TBI 相关机制，并生成假设的新生物标志物候选者。
