Cargando…
Quantifying critical states of complex diseases using single-sample dynamic network biomarkers
Dynamic network biomarkers (DNB) can identify the critical state or tipping point of a disease, thereby predicting rather than diagnosing the disease. However, it is difficult to apply the DNB theory to clinical practice because evaluating DNB at the critical state required the data of multiple samp...
Autores principales: | Liu, Xiaoping, Chang, Xiao, Liu, Rui, Yu, Xiangtian, Chen, Luonan, Aihara, Kazuyuki |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5517040/ https://www.ncbi.nlm.nih.gov/pubmed/28678795 http://dx.doi.org/10.1371/journal.pcbi.1005633 |
Ejemplares similares
-
Identifying critical differentiation state of MCF-7 cells for breast cancer by dynamical network biomarkers
por: Chen, Pei, et al.
Publicado: (2015) -
Detecting early-warning signals for sudden deterioration of complex diseases by dynamical network biomarkers
por: Chen, Luonan, et al.
Publicado: (2012) -
Detection for disease tipping points by landscape dynamic network biomarkers
por: Liu, Xiaoping, et al.
Publicado: (2019) -
Identifying early-warning signals of critical transitions with strong noise by dynamical network markers
por: Liu, Rui, et al.
Publicado: (2015) -
Identifying critical transitions and their leading biomolecular networks in complex diseases
por: Liu, Rui, et al.
Publicado: (2012)