Xiaozhe Hu

This paper introduces a faster approximation of the IsoRank method for aligning large biological networks, achieving comparable accuracy with significantly reduced computational time.

MELISSA improves protein function prediction by integrating functional labels during embedding, outperforming existing methods in yeast and human networks.

The paper evaluates module identification methods across disease-relevant networks using GWAS data to identify top-performing algorithms and disease-associated modules.