Several Indicators of Critical Transitions for Complex Diseases Based on Stochastic Analysis.

ABSTRACT: Many complex diseases (chronic disease onset, development and differentiation, self-assembly, etc.) are reminiscent of phase transitions in a dynamical system: quantitative changes accumulate largely unnoticed until a critical threshold is reached, which causes abrupt qualitative changes of the system. Understanding such nonlinear behaviors is critical to dissect the multiple genetic/environmental factors that together shape the genetic and physiological landscape underlying basic biological functions and to identify the key driving molecules. Based on stochastic differential equation (SDE) model, we theoretically derive three statistical indicators, that is, coefficient of variation (CV), transformed Pearson's correlation coefficient (TPC), and transformed probability distribution (TPD),

SUBMITTER: Wang G 

PROVIDER: S-EPMC5556999 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature