A new model for the inference of biological entities states: Ternary Entity State Inference System.

ABSTRACT: Understanding the state transitions in biological systems and identifying critical steady states are crucial for investigating disease development and discovering key therapeutic targets. To advance the study of state transitions in specific biological entities, we proposed the Ternary Entity State Inference System (T-ESIS). T-ESIS builds upon the Entity State Inference System by providing richer information on entity states, where states can take values of 0, 1, or 1/2, representing activation, inhibition, and normal states, respectively. This method infers state transition pathways based on interaction relationships and visualizes them through the Entity State Network. Furthermore, the cyclic structures within the Entity State Network capture positive and negative feedback loops, providi

SUBMITTER: Zhao Z 

PROVIDER: S-EPMC11415649 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature