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- research-articleApril 2018
Low Rank Spectral Network Alignment
WWW '18: Proceedings of the 2018 World Wide Web ConferencePages 619–628https://doi.org/10.1145/3178876.3186128Network alignment or graph matching is the classic problem of finding matching vertices between two graphs with applications in network de-anonymization and bioinformatics. There exist a wide variety of algorithms for it, but a challenging scenario for ...
- research-articleNovember 2017
Triangular Alignment TAME: A Tensor-Based Approach for Higher-Order Network Alignment
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Volume 14, Issue 6Pages 1446–1458https://doi.org/10.1109/TCBB.2016.2595583Network alignment has extensive applications in comparative interactomics. Traditional approaches aim to simultaneously maximize the number of conserved edges and the underlying similarity of aligned entities. We propose a novel formulation of the ...
- research-articleOctober 2016
De novo identification of cell type hierarchy with application to compound marker detection
BCB '16: Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health InformaticsPages 251–260https://doi.org/10.1145/2975167.2975193Uncovering biochemical processes that drive the transformation of a totipotent cell into various cell types is essential to our understanding of living systems. This complex machinery determines how tissues differ in terms of their anatomy, physiology, ...
- research-articleDecember 2012
Network Similarity Decomposition (NSD): A Fast and Scalable Approach to Network Alignment
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 24, Issue 12Pages 2232–2243https://doi.org/10.1109/TKDE.2011.174As graph-structured data sets become commonplace, there is increasing need for efficient ways of analyzing such data sets. These analyses include conservation, alignment, differentiation, and discrimination, among others. When defined on general graphs, ...
