• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Scientific reports. >Detecting early-warning signals for sudden deterioration of complex diseases by dynamical network biomarkers
【24h】

Detecting early-warning signals for sudden deterioration of complex diseases by dynamical network biomarkers

机译：通过动态网络生物标记物检测复杂疾病突然恶化的预警信号

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

摘要

Considerable evidence suggests that during the progression of complex diseases, the deteriorations are not necessarily smooth but are abrupt, and may cause a critical transition from one state to another at a tipping point. Here, we develop a model-free method to detect early-warning signals of such critical transitions, even with only a small number of samples. Specifically, we theoretically derive an index based on a dynamical network biomarker (DNB) that serves as a general early-warning signal indicating an imminent bifurcation or sudden deterioration before the critical transition occurs. Based on theoretical analyses, we show that predicting a sudden transition from small samples is achievable provided that there are a large number of measurements for each sample, e.g., high-throughput data. We employ microarray data of three diseases to demonstrate the effectiveness of our method. The relevance of DNBs with the diseases was also validated by related experimental data and functional analysis.. ? 2012 Macmillan Publishers Limited. All rights reserved
机译：大量证据表明，在复杂疾病的发展过程中，恶化并不一定是平稳的，而是突然的，并且可能在临界点从一种状态到另一种状态进行临界过渡。在这里，我们开发了一种无模型的方法，即使只有少量样本，也可以检测到这种临界转变的预警信号。具体来说，我们从理论上基于动态网络生物标记（DNB）得出一个索引，该索引用作一般的预警信号，指示在关键过渡发生之前即将发生的分叉或突然恶化。根据理论分析，我们表明，只要每个样品都有大量测量值，例如高通量数据，就可以预测小样品的突然转变。我们采用三种疾病的微阵列数据来证明我们方法的有效性。通过相关的实验数据和功能分析也验证了DNB与疾病的相关性。 2012 Macmillan Publishers Limited。版权所有

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