ArticleNucleic acids research2025
ClusterONE Web: a tool for discovering and analyzing overlapping protein complexes.
Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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
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Who cites it
3 citing papers in PubMed.
- Connectivity patterns in the DMN that are impacted by traumatic stress.Research square · 2026Article
- Genomic analysis of prophages from Burkholderia gladioli exposes extensive genetic diversity.BMC genomics · 2026Article
- Identification and validation of tumor microenvironment-related therapeutic targets in gastric cancer using integrated multi-omics and molecular docking approaches.Frontiers in bioinformatics · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Protein-protein interactions (PPIs) are central to many cellular processes, and the assembly of proteins into complexes is essential for biological function. Clustering with overlapping neighborhood expansion (ClusterONE) has been successfully used to detect overlapping protein complexes in both weighted and unweighted PPI networks. Here, we present ClusterONE Web, a freely available, web-based tool that brings the functionality of ClusterONE into an accessible, user-friendly environment. The platform includes a database of preprocessed PPI datasets covering multiple organisms, reducing the need for manual data collection and preprocessing, while also allowing users to upload their own interaction data. Detected complexes are presented through an interactive interface, facilitating their exploration without requiring specialized software installation. The server also provides built-in Gene Ontology enrichment analysis to aid in the functional interpretation of identified complexes. ClusterONE Web is platform-independent and available at https://paccanarolab.org/clusteroneweb/.
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Registered trials
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