蛋白质组学数据的拓扑分析

David Gnabasik, G. Alaghband
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引用次数: 0

摘要

细胞变得不受调节是因为它们相互作用的拓扑特性使它们不可能被调节。为了探索这一假设,二维PAGE凝胶电泳蛋白浓度测定数据被嵌入并在拓扑计算框架中进行分析。这些2-D PAGE数据是使用标准化、已建立并广泛使用的协议生成的。这些数据也精确、具体、可靠地与内部参考标准一起校准,使数据易于比较。重要的是,蛋白质浓度数据保留了局部相互作用的影响,这使得拓扑分析成为可能。蛋白质行为模型是从蛋白质样品浓度变化的纵向研究中发展起来的。蛋白质相互作用行为的连续变化及其变化率显示出蛋白质浓度的不连续相移。初步数据表明,对癌细胞蛋白质数据的拓扑分析揭示了蛋白质行为空间的不连续性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Topological analysis of proteomic data
Cells become unregulated because topological properties of their interactive behavior make it impossible for them to be regulated. To explore this hypothesis, 2-D PAGE gel electrophoresis protein concentration assay data is embedded and analyzed within a topological computing framework. These 2-D PAGE data are produced using protocols that are standardized, established and widely used. These data are also precise, specific and reliably calibrated alongside an internal reference standard, making the data readily comparable. Importantly, protein concentration data preserve the influence of local interactions, which makes possible a topological analysis. Protein behavior models are developed from longitudinal studies of changes in protein sample concentrations. Continuous variations in protein interactive behavior and their rates of change are shown to produce discontinuous phase shifts in protein concentrations. Preliminary data indicate that a topological analysis of protein data from cancerous cells expose discontinuities in protein behavior space.
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