Network-based anomaly detection algorithm reveals proteins with major roles in human tissues.

ABSTRACT:

Background

Proteins act through physical interactions with other molecules to maintain organismal health. Protein-protein interaction (PPI) networks have proved to be a powerful framework for obtaining insight into protein functions, cellular organization, response to signals, and disease states. In multicellular organisms, protein content varies between tissues, influencing tissue morphology and function. Weighted PPI networks, reflecting the likelihood of interactions in specific tissues, offer insights into tissue-specific processes and disease mechanisms. We hypothesized that detecting anomalous nodes in these networks could reveal proteins with key tissue-specific functions.

Results

Here, we introduce Weighted Graph Anomalous Node Detection (WGAND), a novel machine-lear

SUBMITTER: Kagan D 

PROVIDER: S-EPMC11976396 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature