Affiliation:
1. School of Mathematics, South China University of Technology , Guangzhou 510640, China
2. School of Mathematics and Big Data, Foshan University , Foshan 528000, China
3. School of Computer Science and Engineering, South China University of Technology , Guangzhou 510640, China
Abstract
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.
Funder
National Natural Science Foundation of China
Guangdong Basic and Applied Basic Research Foundation
Publisher
Oxford University Press (OUP)
Subject
Molecular Biology,Information Systems
Cited by
6 articles.
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