ArticleBioinformatics (Oxford, England)2012
Global network alignment using multiscale spectral signatures.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
45 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
- Joint embedding of biological networks for cross-species functional alignment.Bioinformatics (Oxford, England) · 2023Article
- Supervised biological network alignment with graph neural networks.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
- 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
- The protein-protein interaction network alignment using recurrent neural network.Medical & biological engineering & computing · 2021Article
- NetQuilt: deep multispecies network-based protein function prediction using homology-informed network similarity.Bioinformatics (Oxford, England) · 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
- Comparative Analyses of Gene Co-expression Networks: Implementations and Applications in the Study of Evolution.Frontiers in genetics · 2021Review
- AligNet: alignment of protein-protein interaction networks.BMC bioinformatics · 2020Article
- SAlign-a structure aware method for global PPI network alignment.BMC bioinformatics · 2020Article
- L-HetNetAligner: A novel algorithm for Local Alignment of Heterogeneous Biological Networks.Scientific reports · 2020Article
- Pairwise Versus Multiple Global Network Alignment.IEEE access : practical innovations, open solutions · 2020Article
- A review of protein-protein interaction network alignment: From pathway comparison to global alignment.Computational and structural biotechnology journal · 2020Review
- NAIGO: An Improved Method to Align PPI Networks Based on Gene Ontology and Graphlets.Frontiers in bioengineering and biotechnology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
motivationProtein interaction networks provide an important system-level view of biological processes. One of the fundamental problems in biological network analysis is the global alignment of a pair of networks, which puts the proteins of one network into correspondence with the proteins of another network in a manner that conserves their interactions while respecting other evidence of their homology. By providing a mapping between the networks of different species, alignments can be used to inform hypotheses about the functions of unannotated proteins, the existence of unobserved interactions, the evolutionary divergence between the two species and the evolution of complexes and pathways.
resultsWe introduce GHOST, a global pairwise network aligner that uses a novel spectral signature to measure topological similarity between subnetworks. It combines a seed-and-extend global alignment phase with a local search procedure and exceeds state-of-the-art performance on several network alignment tasks. We show that the spectral signature used by GHOST is highly discriminative, whereas the alignments it produces are also robust to experimental noise. When compared with other recent approaches, we find that GHOST is able to recover larger and more biologically significant, shared subnetworks between species. AVAILABILITY: An efficient and parallelized implementation of GHOST, released under the Apache 2.0 license, is available at http://cbcb.umd.edu/kingsford_group/ghost CONTACT: rob@cs.umd.edu.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.