ArticlePloS one2020
NAPAbench 2: A network synthesis algorithm for generating realistic protein-protein interaction (PPI) network families.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 8 citations in OpenAlex.
- Untangling the Complexity of Binding Across Biomolecular Interfaces with Interaction Network Models.Methods in molecular biology (Clifton, N.J.) · 2026Article
- SAMNA: accurate alignment of multiple biological networks based on simulated annealing.Journal of integrative bioinformatics · 2023Article
- pyProGA-A PyMOL plugin for protein residue network analysis.PloS one · 2021Article
- Pairwise Biological Network Alignment Based on Discrete Bat Algorithm.Computational and mathematical methods in medicine · 2021Article
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Authors and funding
3 authors at 3 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
Comparative network analysis provides effective computational means for gaining novel insights into the structural and functional compositions of biological networks. In recent years, various methods have been developed for biological network alignment, whose main goal is to identify important similarities and critical differences between networks in terms of their topology and composition. A major impediment to advancing network alignment techniques has been the lack of gold-standard benchmarks that can be used for accurate and comprehensive performance assessment of such algorithms. The original NAPAbench (network alignment performance assessment benchmark) was developed to address this problem, and it has been widely utilized by many researchers for the development, evaluation, and comparison of novel network alignment techniques. In this work, we introduce NAPAbench 2-a major update of the original NAPAbench that was introduced in 2012. NAPAbench 2 includes a completely redesigned network synthesis algorithm that can generate protein-protein interaction (PPI) network families whose characteristics closely match those of the latest real PPI networks. Furthermore, the network synthesis algorithm comes with an intuitive GUI that allows users to easily generate PPI network families with an arbitrary number of networks of any size, according to a flexible user-defined phylogeny. In addition, NAPAbench 2 provides updated benchmark datasets-created using the redesigned network synthesis algorithm-which can be used for comprehensive performance assessment of network alignment algorithms and their scalability.
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