W. M. Liu

This paper introduces SGTCCA-Net, a framework for multi-omics network inference that addresses limitations of existing methods by incorporating higher-order correlations and improving computational efficiency.

The paper identifies proteomic networks and genetic variants associated with smoking and COPD phenotypes using multi-ethnic proteomic data and network-based GWAS.

SmCCNet 2.0 integrates multi-omics data with a phenotype to reconstruct networks specific to that phenotype, offering improved setup flexibility and user experience.