ArticlePloS one2013
SMETANA: accurate and scalable algorithm for probabilistic alignment of large-scale biological networks.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
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- Molecular similarity: Theory, applications, and perspectives.Artificial intelligence chemistry · 2024Article
- Disentangling the microbial genomic traits associated with aromatic hydrocarbon degradation in a jet fuel-contaminated aquifer.Biodegradation · 2024Article
- Using metabolic networks to predict cross-feeding and competition interactions between microorganisms.Microbiology spectrum · 2024Article
- Network-Based Structural Alignment of RNA Sequences Using TOPAS.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Challenges and Limitations of Biological Network Analysis.Biotech (Basel (Switzerland)) · 2022Article
- An Extensive Assessment of Network Embedding in PPI Network Alignment.Entropy (Basel, Switzerland) · 2022Article
- MUNDO: protein function prediction embedded in a multispecies world.Bioinformatics advances · 2022Article
- ClusterM: a scalable algorithm for computational prediction of conserved protein complexes across multiple protein interaction networks.BMC genomics · 2020Article
- Twadn: an efficient alignment algorithm based on time warping for pairwise dynamic networks.BMC bioinformatics · 2020Article
- Pairwise Versus Multiple Global Network Alignment.IEEE access : practical innovations, open solutions · 2020Article
- NAPAbench 2: A network synthesis algorithm for generating realistic protein-protein interaction (PPI) network families.PloS one · 2020Article
- A review of protein-protein interaction network alignment: From pathway comparison to global alignment.Computational and structural biotechnology journal · 2020Review
- Data-driven network alignment.PloS one · 2020Article
- A novel algorithm for alignment of multiple PPI networks based on simulated annealing.BMC genomics · 2019Article
- LePrimAlign: local entropy-based alignment of PPI networks to predict conserved modules.BMC genomics · 2019Article
- Identification of co-evolving temporal networks.BMC genomics · 2019Article
- WebNetCoffee: a web-based application to identify functionally conserved proteins from Multiple PPI networks.BMC bioinformatics · 2018Article
- PrimAlign: PageRank-inspired Markovian alignment for large biological networks.Bioinformatics (Oxford, England) · 2018Article
- CUFID-query: accurate network querying through random walk based network flow estimation.BMC bioinformatics · 2017Article
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2 authors.
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Abstract
In this paper we introduce an efficient algorithm for alignment of multiple large-scale biological networks. In this scheme, we first compute a probabilistic similarity measure between nodes that belong to different networks using a semi-Markov random walk model. The estimated probabilities are further enhanced by incorporating the local and the cross-species network similarity information through the use of two different types of probabilistic consistency transformations. The transformed alignment probabilities are used to predict the alignment of multiple networks based on a greedy approach. We demonstrate that the proposed algorithm, called SMETANA, outperforms many state-of-the-art network alignment techniques, in terms of computational efficiency, alignment accuracy, and scalability. Our experiments show that SMETANA can easily align tens of genome-scale networks with thousands of nodes on a personal computer without any difficulty. The source code of SMETANA is available upon request. The source code of SMETANA can be downloaded from http://www.ece.tamu.edu/~bjyoon/SMETANA/.
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