ArticleBioinformatics (Oxford, England)2014
HubAlign: an accurate and efficient method for global alignment of protein-protein interaction networks.
Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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29 citing papers in PubMed.
- Ten practical tips and tricks to improve the effectiveness of biological network alignment.PLoS computational biology · 2025Article
- Exact p-values for global network alignments via combinatorial analysis of shared GO terms : REFANGO: Rigorous Evaluation of Functional Alignments of Networks using Gene Ontology.Journal of mathematical biology · 2024Article
- SAMNA: accurate alignment of multiple biological networks based on simulated annealing.Journal of integrative bioinformatics · 2023Article
- Joint embedding of biological networks for cross-species functional alignment.Bioinformatics (Oxford, England) · 2023Article
- Network-Based Structural Alignment of RNA Sequences Using TOPAS.Methods in molecular biology (Clifton, N.J.) · 2023Article
- SANA: cross-species prediction of Gene Ontology GO annotations via topological network alignment.NPJ systems biology and applications · 2022Article
- MUNDO: protein function prediction embedded in a multispecies world.Bioinformatics advances · 2022Article
- BioAlign: An Accurate Global PPI Network Alignment Algorithm.Evolutionary bioinformatics online · 2022Article
- The protein-protein interaction network alignment using recurrent neural network.Medical & biological engineering & computing · 2021Article
- Juxtapose: a gene-embedding approach for comparing co-expression networks.BMC bioinformatics · 2021Article
- Pairwise Biological Network Alignment Based on Discrete Bat Algorithm.Computational and mathematical methods in medicine · 2021Article
- Predicting Protein Functions Based on Differential Co-expression and Neighborhood Analysis.Journal of computational biology : a journal of computational molecular cell biology · 2021Article
- Comparative Analyses of Gene Co-expression Networks: Implementations and Applications in the Study of Evolution.Frontiers in genetics · 2021Review
- Alignment of biological networks by integer linear programming: virus-host protein-protein interaction networks.BMC bioinformatics · 2020Article
- AligNet: alignment of protein-protein interaction networks.BMC bioinformatics · 2020Article
- SAlign-a structure aware method for global PPI network alignment.BMC bioinformatics · 2020Article
- Alignment of virus-host protein-protein interaction networks by integer linear programming: SARS-CoV-2.PloS one · 2020Article
- Data-driven network alignment.PloS one · 2020Article
- Functional protein representations from biological networks enable diverse cross-species inference.Nucleic acids research · 2019Article
- Discovering large conserved functional components in global network alignment by graph matching.BMC genomics · 2018Article
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2 authors.
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Abstract
motivationHigh-throughput experimental techniques have produced a large amount of protein-protein interaction (PPI) data. The study of PPI networks, such as comparative analysis, shall benefit the understanding of life process and diseases at the molecular level. One way of comparative analysis is to align PPI networks to identify conserved or species-specific subnetwork motifs. A few methods have been developed for global PPI network alignment, but it still remains challenging in terms of both accuracy and efficiency.
resultsThis paper presents a novel global network alignment algorithm, denoted as HubAlign, that makes use of both network topology and sequence homology information, based upon the observation that topologically important proteins in a PPI network usually are much more conserved and thus, more likely to be aligned. HubAlign uses a minimum-degree heuristic algorithm to estimate the topological and functional importance of a protein from the global network topology information. Then HubAlign aligns topologically important proteins first and gradually extends the alignment to the whole network. Extensive tests indicate that HubAlign greatly outperforms several popular methods in terms of both accuracy and efficiency, especially in detecting functionally similar proteins. AVAILABILITY: HubAlign is available freely for non-commercial purposes at http://ttic.uchicago.edu/∼hashemifar/software/HubAlign.zip. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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