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

ABSTRACT: 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-throughp

SUBMITTER: Chen L 

PROVIDER: S-EPMC3314989 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature