Protein structural domain-disease association prediction based on heterogeneous networks.

ABSTRACT:

Background

Domains can be viewed as portable units of protein structure, folding, function, evolution, and design. Small proteins are often found to be composed of only a single domain, while most large proteins consist of multiple domains for achieving various composite cellular functions. A dysfunction in domains may affect the function of proteins in some disease. Inferring the disease-related domains will help our understanding of the mechanism of human complex diseases.

Results

In this study, we firstly build a global heterogeneous information network based on structural-based domains, proteins, and diseases. Then the topological features of the network are extracted according to the meta-paths between domain and disease nodes. Finally, we train a binary classifier base

SUBMITTER: Zhang J 

PROVIDER: S-EPMC11987217 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature