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Found 6 papers, 4 papers with code
New GO-based Measures and Their Statistical Significance in Multiple Network Alignment
In this paper, we propose two new measures, the Squared GO Score (SGS) and the Exposed G Score, to evaluate the quality of multiple network alignments while using functional information from Gene Ontology (GO) terms.
BLANT: Basic Local Alignment of Network Topology, Part 2: Topology-only Extension Beyond Graphlet Seeds
While topology-driven local network alignment has a wide variety of potential applications outside bioinformatics, here we focus on the alignment of Protein-Protein Interaction (PPI) networks.
SANA: Cross-Species Prediction of Gene Ontology GO Annotations via Topological Network Alignment
We argue that this failure of topology alone is due to the sparsity and incompleteness of the PPI network data of almost all species, which provides the network topology with a small signal-to-noise ratio that is effectively swamped when sequence information is added to the mix.
On the current failure -- but bright future -- of topology-driven biological network alignment
The function of a protein is defined by its interaction partners.
Exact $p$-values for global network alignments via combinatorial analysis of shared GO terms (Subtitle: REFANGO: Rigorous Evaluation of Functional Alignments of Networks using Gene Ontology)
Network alignment aims to uncover topologically similar regions in the protein-protein interaction (PPI) networks of two or more species under the assumption that topologically similar regions tend to perform similar functions.
An introductory guide to aligning networks using SANA, the Simulated Annealing Network Aligner
SANA is one of many algorithms proposed for the arena of biological network alignment.
