Before revision:  In evaluations on synthetic networks and real-world biological network data , our proposed heterogeneous NA methods lead to higher-quality alignments and better robustness to noise in the data than their homogeneous counterparts  .
After revision:  In evaluations on synthetic networks and real-world biological network data , our proposed heterogeneous NA methods lead to higher-quality alignments and better robustness to noise in the data than their homogeneous counterparts . The software and data from this work is available upon request .