• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IFAC PapersOnLine >Periodicity Scoring of Time Series Encodes Dynamical Behavior of the Tumor Suppressor p53 ? ?
【24h】

Periodicity Scoring of Time Series Encodes Dynamical Behavior of the Tumor Suppressor p53 ? ?

机译：时间序列的周期性评分编码肿瘤抑制器P53的动态行为p53 ？ ？

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper we analyze the dynamical behavior of the tumor suppressor protein p53, an essential player in the cellular stress response, which prevents a cell from dividing if severe DNA damage is present. When this response system is malfunctioning, e.g. due to mutations in p53, uncontrolled cell proliferation may lead to the development of cancer. Understanding the behavior of p53 is thus crucial to prevent its failing. It has been shown in various experiments that periodicity of the p53 signal is one of the main descriptors of its dynamics, and that its pulsing behavior (regular vs. spontaneous) indicates the level and type of cellular stress. In the present work, we introduce an algorithm to score the local periodicity of a given time series (such as the p53 signal), which we callDetrended Autocorrelation Periodicity Scoring(DAPS). It applies pitch detection (via autocorrelation) on sliding windows of the entire time series to describe the overall periodicity by a distribution of localized pitch scores. We apply DAPS to the p53 time series obtained from single cell experiments and establish a correlation between the periodicity scoring of a cell’s p53 signal and the number of cell division events. In particular, we show that high periodicity scoring of p53 is correlated to a low number of cell divisions and vice versa. We show similar results with a more computationally intensive state-of-the-art periodicity scoring algorithm based on topology known as Sw1PerS. This correlation has two major implications: It demonstrates that periodicity scoring of the p53 signal is a good descriptor for cellular stress, and it connects the high variability of p53 periodicity observed in cell populations to the variability in the number of cell division events.
机译：在本文中，我们分析了肿瘤抑制蛋白P53的动态行为，细胞应激反应中的必要运动员，如果存在严重的DNA损伤，可以防止细胞分开。当这个响应系统发生故障时，例如由于P53中的突变，不受控制的细胞增殖可能导致癌症的发育。因此，了解P53的行为对于防止其失败是至关重要的。已经在各种实验中示出了P53信号的周期性是其动态的主要描述符之一，并且其脉冲行为（常规与自发性）表示蜂窝应力的水平和类型。在本作工作中，我们介绍了一种算法来得分给定时间序列（例如P53信号）的局部周期，我们调用自相关周期评分（DAP）。它在整个时间序列的滑动窗口上应用音调检测（通过自相关），以通过分布本地化间距分数来描述整体周期性。我们将DAP应用于从单个小区实验获得的P53时间序列，并在细胞P53信号的周期性评分与细胞分裂事件的数量之间建立相关性。特别地，我们表明p53的高周期评分与少量的细胞分区相关，反之亦然。我们与基于SW1Pers称为SW1Pers称为SW1Pers的拓扑的更加计算密集的最新状态评分算法，我们展示了类似的结果。这种相关性具有两个主要影响：它表明P53信号的周期性评分是对细胞应激的良好描述符，并且它将在细胞群中观察到的P53周期性的高可变性与细胞分裂事件数量的变异性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号