ArticleScientific reports2017
Functional diversity of topological modules in human protein-protein interaction networks.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- KDGene: knowledge graph completion for disease gene prediction using interactional tensor decomposition.Briefings in bioinformatics · 2024Article
- Protein interaction networks provide insight into fetal origins of chronic obstructive pulmonary disease.Respiratory research · 2022Article
- Entropy-Based Graph Clustering of PPI Networks for Predicting Overlapping Functional Modules of Proteins.Entropy (Basel, Switzerland) · 2021Article
- A network-based machine-learning framework to identify both functional modules and disease genes.Human genetics · 2021Article
- Article
- Performance Assessment of the Network Reconstruction Approaches on Various Interactomes.Frontiers in molecular biosciences · 2021Article
- Network-based method for drug target discovery at the isoform level.Scientific reports · 2019Article
- It is time to apply biclustering: a comprehensive review of biclustering applications in biological and biomedical data.Briefings in bioinformatics · 2019Review
- Discovery and characterization of functional modules associated with body weight in broilers.Scientific reports · 2019Article
- Functional homogeneity and specificity of topological modules in human proteome.BMC bioinformatics · 2019Article
- A Comparative Study of Cluster Detection Algorithms in Protein-Protein Interaction for Drug Target Discovery and Drug Repurposing.Frontiers in pharmacology · 2019Article
- Concurrence of form and function in developing networks and its role in synaptic pruning.Nature communications · 2018Article
Corrections and comments
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Authors and funding
5 authors.
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Abstract
A large-scale molecular interaction network of protein-protein interactions (PPIs) enables the automatic detection of molecular functional modules through a computational approach. However, the functional modules that are typically detected by topological community detection algorithms may be diverse in functional homogeneity and are empirically considered to be default functional modules. Thus, a significant challenge that has been described but not elucidated is investigating the relationship between topological modules and functional modules. We systematically investigated this issue by initially using seven widely used community detection algorithms to partition the PPI network into communities. Four homogeneity measures were subsequently implemented to evaluate the functional homogeneity of protein community. We determined that a significant portion of topological modules with heterogeneous functionality exists and should be further investigated; moreover, these findings indicated that topologically based functional module detection approaches must be reconsidered. Furthermore, we found that the functional homogeneity of topological modules is positively correlated with their edge densities, degree of association with diseases and general Gene Ontology (GO) terms. Thus, topologically based module detection approaches should be used with caution in the identification of functional modules with high homogeneity.
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