Drought Stress-Related Gene Identification in Rice by Random Walk with Restart on Multiplex Biological Networks

Drought stress-related gene identification is vital in revealing the drought resistance mechanisms underlying rice and for cultivating rice-resistant varieties. Traditional methods, such as Genome-Wide Association Studies (GWAS), usually identify hundreds of candidate stress genes, further validation by biological experiements then time-consuming laborious. However, computational prioritization methods can effectively reduce number genes. This study introduces a random walk with restart algorithm (RWR), state-of-the-art guilt-by-association method, to operate on multiplex networks. It explores physical functional interactions between molecules at different levels prioritizes set potential Firstly, we integrated Protein–Protein Interaction (PPI) network, constructed multiple protein interaction data, coexpression network into network. Then, implemented RWR networks (RWR-M) known genes seed nodes Finally, conducted association analysis Thirteen were identified five which have been reported recent literature be involved mechanisms.