Journal
SCIENTIFIC REPORTS
Volume 2, Issue -, Pages -Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/srep00342
Keywords
-
Categories
Funding
- NSFC [91029301, 61134013, 61072149, 31100949]
- Shanghai Pujiang Program
- SIBS of CAS [2009CSP002, 2011KIP203]
- CAS [KSCX2-EW-R-01]
- National Center for Mathematics and Interdisciplinary Sciences of CAS
- JSPS/CSTP
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available