摘要
很多生物系统的动态发展过程中都存在状态的临界迁移现象,例如复杂疾病,在离临界状态较远时,病情不明显;而到达临界状态后,病情有可能在很短的时间内从稳定期突然恶化而成为重病期.如何基于高维生物医学数据,找到可用于识别生物系统状态改变临界期的标记物,对包括疾病的早期预警等课题具有重要意义.围绕生物系统临界状态识别与预警这一课题,本文主要综述了动态网络生物标志物(DNB)方法,及针对不同的数据条件所发展的一系列适用的改进方法及其应用.
Many biological systems exhibit critical transitions in their dynamic development processes.For instance,in complex diseases,the condition may not be apparent when far from the critical state;however,upon reaching the critical state,the condition may rapidly deteriorate from a stable phase to a severe phase.It is of great importance to identify biomarkers from high-dimensional biomedical data that can be used to recognize the critical periods of state changes in biological systems,including early warning of diseases.This paper reviews the methods of dynamic network biomarkers and a series of applicable modified methods developed for different data conditions and their applications in the identification and early warning of critical states in biological systems.
作者
刘锐
杨茜然
LIU Rui;YANG Xiran(School of Mathematics,South China University of Technology,Guangzhou 510640,China)
出处
《中山大学学报(自然科学版)(中英文)》
CAS
CSCD
北大核心
2024年第6期275-290,共16页
Acta Scientiarum Naturalium Universitatis Sunyatseni
基金
国家自然科学基金(62172164,12026608)。