BannMI deciphers potential n-to-1 information transduction in signaling pathways to unravel message of intrinsic apoptosis.

ABSTRACT:

Motivation

Cell fate decisions, such as apoptosis or proliferation, are communicated via signaling pathways. The pathways are heavily intertwined and often consist of sequential interaction of proteins (kinases). Information integration takes place on the protein level via n-to-1 interactions. A state-of-the-art procedure to quantify information flow (edges) between signaling proteins (nodes) is network inference. However, edge weight calculation typically refers to 1-to-1 interactions only and relies on mean protein phosphorylation levels instead of single cell distributions. Information theoretic measures such as the mutual information (MI) have the potential to overcome these shortcomings but are still rarely used.

Results

This work proposes a Bayesian nearest neig

SUBMITTER: Schmidt B 

PROVIDER: S-EPMC10769817 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature