ArticleBioinformatics (Oxford, England)2013
Optimizing a global alignment of protein interaction networks.
Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- 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
- Supervised biological network alignment with graph neural networks.Bioinformatics (Oxford, England) · 2023Article
- The protein-protein interaction network alignment using recurrent neural network.Medical & biological engineering & computing · 2021Article
- SAlign-a structure aware method for global PPI network alignment.BMC bioinformatics · 2020Article
- A review of protein-protein interaction network alignment: From pathway comparison to global alignment.Computational and structural biotechnology journal · 2020Review
- Unified Alignment of Protein-Protein Interaction Networks.Scientific reports · 2017Article
- The post-genomic era of biological network alignment.EURASIP journal on bioinformatics & systems biology · 2015Article
- L-GRAAL: Lagrangian graphlet-based network aligner.Bioinformatics (Oxford, England) · 2015Article
- HubAlign: an accurate and efficient method for global alignment of protein-protein interaction networks.Bioinformatics (Oxford, England) · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
motivationThe global alignment of protein interaction networks is a widely studied problem. It is an important first step in understanding the relationship between the proteins in different species and identifying functional orthologs. Furthermore, it can provide useful insights into the species' evolution.
resultsWe propose a novel algorithm, PISwap, for optimizing global pairwise alignments of protein interaction networks, based on a local optimization heuristic that has previously demonstrated its effectiveness for a variety of other intractable problems. PISwap can begin with different types of network alignment approaches and then iteratively adjust the initial alignments by incorporating network topology information, trading it off for sequence information. In practice, our algorithm efficiently refines other well-studied alignment techniques with almost no additional time cost. We also show the robustness of the algorithm to noise in protein interaction data. In addition, the flexible nature of this algorithm makes it suitable for different applications of network alignment. This algorithm can yield interesting insights into the evolutionary dynamics of related species. AVAILABILITY: Our software is freely available for non-commercial purposes from our Web site, http://piswap.csail.mit.edu/. CONTACT: bab@csail.mit.edu or csliao@ie.nthu.edu.tw. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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.