ArticleBioinformatics (Oxford, England)2012
Graphlet-based edge clustering reveals pathogen-interacting proteins.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- A New Framework to Empower Ecosystem Assessment Through the Integration of eDNA Inventories, Graph Theory and Niche Modelling.Ecology letters · 2026Article
- Combining graphlets and random walks for capturing complex network topology.Scientific reports · 2026Article
- Current and future directions in network biology.Bioinformatics advances · 2024Article
- Multi-layer sequential network analysis improves protein 3D structural classification.Proteins · 2022Article
- Directed closure coefficient and its patterns.PloS one · 2021Article
- Protein Function Prediction Based on PPI Networks: Network Reconstruction vs Edge Enrichment.Frontiers in genetics · 2021Article
- Network-based protein structural classification.Royal Society open science · 2020Article
- WIPER: Weighted in-Path Edge Ranking for biomolecular association networks.Quantitative biology (Beijing, China) · 2019Article
- From homogeneous to heterogeneous network alignment via colored graphlets.Scientific reports · 2018Article
- ClueNet: Clustering a temporal network based on topological similarity rather than denseness.PloS one · 2018Article
- GRAFENE: Graphlet-based alignment-free network approach integrates 3D structural and sequence (residue order) data to improve protein structural comparison.Scientific reports · 2017Article
- Identification of protein complexes by integrating multiple alignment of protein interaction networks.Bioinformatics (Oxford, England) · 2017Article
- Efficient orbit-aware triad and quad census in directed and undirected graphs.Applied network science · 2017Article
- SCOUT: simultaneous time segmentation and community detection in dynamic networks.Scientific reports · 2016Article
- Article
- The post-genomic era of biological network alignment.EURASIP journal on bioinformatics & systems biology · 2015Article
- Proper evaluation of alignment-free network comparison methods.Bioinformatics (Oxford, England) · 2015Article
- Exploring the structure and function of temporal networks with dynamic graphlets.Bioinformatics (Oxford, England) · 2015Article
- Mining host-pathogen protein interactions to characterize Burkholderia mallei infectivity mechanisms.PLoS computational biology · 2015Article
- Fair evaluation of global network aligners.Algorithms for molecular biology : AMB · 2015Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
motivationPrediction of protein function from protein interaction networks has received attention in the post-genomic era. A popular strategy has been to cluster the network into functionally coherent groups of proteins and assign the entire cluster with a function based on functions of its annotated members. Traditionally, network research has focused on clustering of nodes. However, clustering of edges may be preferred: nodes belong to multiple functional groups, but clustering of nodes typically cannot capture the group overlap, while clustering of edges can. Clustering of adjacent edges that share many neighbors was proposed recently, outperforming different node clustering methods. However, since some biological processes can have characteristic 'signatures' throughout the network, not just locally, it may be of interest to consider edges that are not necessarily adjacent.
resultsWe design a sensitive measure of the 'topological similarity' of edges that can deal with edges that are not necessarily adjacent. We cluster edges that are similar according to our measure in different baker's yeast protein interaction networks, outperforming existing node and edge clustering approaches. We apply our approach to the human network to predict new pathogen-interacting proteins. This is important, since these proteins represent drug target candidates. AVAILABILITY: Software executables are freely available upon request. CONTACT: tmilenko@nd.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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