ArticleScientific reports2013
Improved network community structure improves function prediction.
Article in Scientific reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Network analysis of serotonin CNVs shows biological convergence from genetic heterogeneity and discriminates between autism and developmental delay.Scientific reports · 2026Article
- Improving temporal smoothness and snapshot quality in dynamic network community discovery using NOME algorithm.PeerJ. Computer science · 2023Article
- PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide Predictions.Frontiers in immunology · 2018Article
- AIPpred: Sequence-Based Prediction of Anti-inflammatory Peptides Using Random Forest.Frontiers in pharmacology · 2018Article
- Inverse Resolution Limit of Partition Density and Detecting Overlapping Communities by Link-Surprise.Scientific reports · 2017Article
- MLACP: machine-learning-based prediction of anticancer peptides.Oncotarget · 2017Article
- Global organization of a binding site network gives insight into evolution and structure-function relationships of proteins.Scientific reports · 2017Article
- Finding multiple reaction pathways via global optimization of action.Nature communications · 2017Article
- Large-scale identification of human protein function using topological features of interaction network.Scientific reports · 2016Article
- An efficient method for protein function annotation based on multilayer protein networks.Human genomics · 2016Article
- Integrative analysis of human protein, function and disease networks.Scientific reports · 2015Article
- Sigma-RF: prediction of the variability of spatial restraints in template-based modeling by random forest.BMC bioinformatics · 2015Article
- Community-based network study of protein-carbohydrate interactions in plant lectins using glycan array data.PloS one · 2014Article
- Community structure detection for overlapping modules through mathematical programming in protein interaction networks.PloS one · 2014Article
- Random forest-based protein model quality assessment (RFMQA) using structural features and potential energy terms.PloS one · 2014Article
- Discovering link communities in complex networks by an integer programming model and a genetic algorithm.PloS one · 2013Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We are overwhelmed by experimental data, and need better ways to understand large interaction datasets. While clustering related nodes in such networks-known as community detection-appears a promising approach, detecting such communities is computationally difficult. Further, how to best use such community information has not been determined. Here, within the context of protein function prediction, we address both issues. First, we apply a novel method that generates improved modularity solutions than the current state of the art. Second, we develop a better method to use this community information to predict proteins' functions. We discuss when and why this community information is important. Our results should be useful for two distinct scientific communities: first, those using various cost functions to detect community structure, where our new optimization approach will improve solutions, and second, those working to extract novel functional information about individual nodes from large interaction datasets.
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