Identifying the critical state of cancers by single-sample Markov flow entropy.

ABSTRACT:

Background

The progression of complex diseases sometimes undergoes a drastic critical transition, at which the biological system abruptly shifts from a relatively healthy state (before-transition stage) to a disease state (after-transition stage). Searching for such a critical transition or critical state is crucial to provide timely and effective scientific treatment to patients. However, in most conditions where only a small sample size of clinical data is available, resulting in failure when detecting the critical states of complex diseases, particularly only single-sample data.

Methods

In this study, different from traditional methods that require multiple samples at each time, a model-free computational method, single-sample Markov flow entropy (sMFE), provides a soluti

SUBMITTER: Liu J 

PROVIDER: S-EPMC10373650 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature