ArticlePloS one2014
GASOLINE: a Greedy And Stochastic algorithm for optimal Local multiple alignment of Interaction NEtworks.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Computationally Reconstructed Interactome ofInternational journal of molecular sciences · 2021Article
- GRAPES-DD: exploiting decision diagrams for index-driven search in biological graph databases.BMC bioinformatics · 2021Article
- NAPAbench 2: A network synthesis algorithm for generating realistic protein-protein interaction (PPI) network families.PloS one · 2020Article
- Protein folding prediction in the HP model using ions motion optimization with a greedy algorithm.BioData mining · 2018Article
- SEQUOIA: significance enhanced network querying through context-sensitive random walk and minimization of network conductance.BMC systems biology · 2017Article
- Incorporating topological information for predicting robust cancer subnetwork markers in human protein-protein interaction network.BMC bioinformatics · 2016Article
- Creating, generating and comparing random network models with NetworkRandomizer.F1000Research · 2016Article
- NetMatchStar: an enhanced Cytoscape network querying app.F1000Research · 2015Article
- DT-Web: a web-based application for drug-target interaction and drug combination prediction through domain-tuned network-based inference.BMC systems biology · 2015Article
- SPECTRA: An Integrated Knowledge Base for Comparing Tissue and Tumor-Specific PPI Networks in Human.Frontiers in bioengineering and biotechnology · 2015Article
- Proteins comparison through probabilistic optimal structure local alignment.Frontiers in genetics · 2014Article
- GASOLINE: a Cytoscape app for multiple local alignment of PPI networks.F1000Research · 2014Article
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4 authors.
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Abstract
The analysis of structure and dynamics of biological networks plays a central role in understanding the intrinsic complexity of biological systems. Biological networks have been considered a suitable formalism to extend evolutionary and comparative biology. In this paper we present GASOLINE, an algorithm for multiple local network alignment based on statistical iterative sampling in connection to a greedy strategy. GASOLINE overcomes the limits of current approaches by producing biologically significant alignments within a feasible running time, even for very large input instances. The method has been extensively tested on a database of real and synthetic biological networks. A comprehensive comparison with state-of-the art algorithms clearly shows that GASOLINE yields the best results in terms of both reliability of alignments and running time on real biological networks and results comparable in terms of quality of alignments on synthetic networks. GASOLINE has been developed in Java, and is available, along with all the computed alignments, at the following URL: http://ferrolab.dmi.unict.it/gasoline/gasoline.html.
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