Arrell D Kent, Terzic Andre
Circ Cardiovasc Genet. 2012 Aug 1;5(4):478. doi: 10.1161/CIRCGENETICS.110.958991.
Universal principles underlying network science, and their ever-increasing applications in biomedicine, underscore the unprecedented capacity of systems biology based strategies to synthesize and resolve massive high throughput generated datasets. Enabling previously unattainable comprehension of biological complexity, systems approaches have accelerated progress in elucidating disease prediction, progression, and outcome. Applied to the spectrum of states spanning health and disease, network proteomics establishes a collation, integration, and prioritization algorithm to guide mapping and decoding of proteome landscapes from large-scale raw data. Providing unparalleled deconvolution of protein lists into global interactomes, integrative systems proteomics enables objective, multi-modal interpretation at molecular, pathway, and network scales, merging individual molecular components, their plurality of interactions, and functional contributions for systems comprehension. As such, network systems approaches are increasingly exploited for objective interpretation of cardiovascular proteomics studies. Here, we highlight network systems proteomic analysis pipelines for integration and biological interpretation through protein cartography, ontological categorization, pathway and functional enrichment and complex network analysis.
网络科学的普遍原理及其在生物医学中日益广泛的应用,凸显了基于系统生物学的策略在合成和解析大量高通量生成数据集方面前所未有的能力。系统方法能够实现对生物复杂性前所未有的理解,加快了在阐明疾病预测、进展和结果方面的进展。网络蛋白质组学应用于涵盖健康和疾病的各种状态,建立了一种整理、整合和优先级排序算法,以指导从大规模原始数据中绘制和解读蛋白质组图谱。整合系统蛋白质组学能够将蛋白质列表无与伦比地解卷积为全局相互作用组,在分子、通路和网络尺度上实现客观的多模态解释,融合单个分子成分、它们的多种相互作用以及功能贡献,以实现系统理解。因此,网络系统方法越来越多地被用于心血管蛋白质组学研究的客观解释。在这里,我们重点介绍通过蛋白质制图、本体分类、通路和功能富集以及复杂网络分析进行整合和生物学解释的网络系统蛋白质组学分析流程。