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TPD:一种基于动态网络生物标志物的 tipping-point 检测的网络工具。

TPD: a web tool for tipping-point detection based on dynamic network biomarker.

机构信息

School of Mathematics, South China University of Technology, Guangzhou 510640, China.

School of Mathematics and Big Data, Foshan University, Foshan 528000, China.

出版信息

Brief Bioinform. 2022 Sep 20;23(5). doi: 10.1093/bib/bbac399.

DOI:10.1093/bib/bbac399
PMID:36088546
Abstract

Tipping points or critical transitions widely exist during the progression of many biological processes. It is of great importance to detect the tipping point with the measured omics data, which may be a key to achieving predictive or preventive medicine. We present the tipping point detector (TPD), a web tool for the detection of the tipping point during the dynamic process of biological systems, and further its leading molecules or network, based on the input high-dimensional time series or stage course data. With the solid theoretical background of dynamic network biomarker (DNB) and a series of computational methods for DNB detection, TPD detects the potential tipping point/critical state from the input omics data and outputs multifarious visualized results, including a suggested tipping point with a statistically significant P value, the identified key genes and their functional biological information, the dynamic change in the DNB/leading network that may drive the critical transition and the survival analysis based on DNB scores that may help to identify 'dark' genes (nondifferential in terms of expression but differential in terms of DNB scores). TPD fits all current browsers, such as Chrome, Firefox, Edge, Opera, Safari and Internet Explorer. TPD is freely accessible at http://www.rpcomputationalbiology.cn/TPD.

摘要

在许多生物过程的进展中,广泛存在着 tipping points 或 critical transitions。利用测量的组学数据检测 tipping point 非常重要,这可能是实现预测性或预防性医学的关键。我们提出了 tipping point detector(TPD),这是一个基于输入高维时间序列或阶段数据,用于检测生物系统动态过程中 tipping point 的网络工具,进一步还可以检测潜在的 tipping point/critical state 及其主导分子或网络。TPD 基于动态网络生物标志物(DNB)的坚实理论基础和一系列用于 DNB 检测的计算方法,从输入的组学数据中检测潜在的 tipping point,并输出多种可视化结果,包括具有统计学意义的 P 值的建议 tipping point、鉴定的关键基因及其功能生物学信息、可能驱动关键转变的 DNB/leading network 的动态变化,以及基于 DNB 分数的生存分析,这可能有助于识别“暗”基因(表达上无差异,但 DNB 分数上有差异)。TPD 兼容所有当前的浏览器,如 Chrome、Firefox、Edge、Opera、Safari 和 Internet Explorer。TPD 可免费访问,网址为:http://www.rpcomputationalbiology.cn/TPD。

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