Global alignment of multiple protein interaction networks with application to functional orthology detection

By Rohit Singh, Jinbo Xu, Bonnie Berger. Proceedings of the National Academy of Sciences of the United States of America, 2008

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Network propagation: a universal amplifier of genetic associations (2017, methodology): “Similar ideas were used by Isorank 38 and its follow-up, IsoRankN 39 , to predict functional orthology by aligning PPI networks from multiple species.”
Protein-protein interaction prediction via Collective Matrix Factorization (2010, methodology): “We exploit the IsoRank [26] method to construct our similarity matrix S m×n , which can be thought as a particular spectral method for global graph alignment.”
Computational solutions for omics data (2013, methodology): “It has been used to align and to analyse networks based on protein–protein interaction 134,135 , genetic interaction 140 and metabolic data 141 .”
Gromov-Wasserstein Learning for Graph Matching and Node Embedding (2019, methodology): “, matching the protein networks from different species (Sharan & Ideker, 2006; Singh et al., 2008), linking accounts in different social networks (Zhang & Philip, 2015), and feature matching in computer vision (Cordella et al.”
struc2vec: Learning Node Representations from Structural Identity (2017, background): “For example, individuals in a social network have a social role or social position [11, 19], while proteins in a protein-protein interaction (PPI) network exert specic functions [1, 22].”