ArticleBMC bioinformatics2014
Detecting temporal protein complexes from dynamic protein-protein interaction networks.
Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Epitope-guided Detection of a Molecular Glue-induced Ternary Complex Using Engineered Synthetic Antibody Fragments.Journal of molecular biology · 2026Article
- Micro-functional protein complexes mining in biological intelligent computing: a weighted network approach.BMC bioinformatics · 2026Article
- Graph and Hypergraph Theories Applied to Dynamic Protein-Protein Interaction Network Analysis, and Deep-Learning Frameworks for Protein Complex Network Prediction.International journal of molecular sciences · 2026Review
- Recent advances in deep learning for protein-protein interaction: a review.BioData mining · 2025Review
- DyNDG: Identifying Leukemia-related Genes Based on Time-series Dynamic Network by Integrating Differential Genes.Genomics, proteomics & bioinformatics · 2025Article
- Network analysis of multivariate time series data in biological systems: methods and applications.Briefings in bioinformatics · 2025Article
- Temporal GeneTerrain: advancing precision medicine through dynamic gene expression visualization.Frontiers in bioinformatics · 2025Article
- Inferring cell cycle phases from a partially temporal network of protein interactions.Cell reports methods · 2023Article
- Temporal networks in biology and medicine: a survey on models, algorithms, and tools.Network modeling and analysis in health informatics and bioinformatics · 2023Review
- DPCT: A Dynamic Method for Detecting Protein Complexes From TAP-Aware Weighted PPI Network.Frontiers in genetics · 2020Article
- Protein complex detection based on flower pollination mechanism in multi-relation reconstructed dynamic protein networks.BMC bioinformatics · 2019Article
- Identifying Protein Complexes from Dynamic Temporal Interval Protein-Protein Interaction Networks.BioMed research international · 2019Article
- A multi-network clustering method for detecting protein complexes from multiple heterogeneous networks.BMC bioinformatics · 2017Article
- Neighbor Affinity-Based Core-Attachment Method to Detect Protein Complexes in Dynamic PPI Networks.Molecules (Basel, Switzerland) · 2017Article
- Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.PloS one · 2017Article
- Differential network analysis from cross-platform gene expression data.Scientific reports · 2016Article
- Protein complex detection based on partially shared multi-view clustering.BMC bioinformatics · 2016Article
- A two-layer integration framework for protein complex detection.BMC bioinformatics · 2016Article
- Mining Temporal Protein Complex Based on the Dynamic PIN Weighted with Connected Affinity and Gene Co-Expression.PloS one · 2016Article
- BiCAMWI: A Genetic-Based Biclustering Algorithm for Detecting Dynamic Protein Complexes.PloS one · 2016Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundProteins dynamically interact with each other to perform their biological functions. The dynamic operations of protein interaction networks (PPI) are also reflected in the dynamic formations of protein complexes. Existing protein complex detection algorithms usually overlook the inherent temporal nature of protein interactions within PPI networks. Systematically analyzing the temporal protein complexes can not only improve the accuracy of protein complex detection, but also strengthen our biological knowledge on the dynamic protein assembly processes for cellular organization.
resultsIn this study, we propose a novel computational method to predict temporal protein complexes. Particularly, we first construct a series of dynamic PPI networks by joint analysis of time-course gene expression data and protein interaction data. Then a Time Smooth Overlapping Complex Detection model (TS-OCD) has been proposed to detect temporal protein complexes from these dynamic PPI networks. TS-OCD can naturally capture the smoothness of networks between consecutive time points and detect overlapping protein complexes at each time point. Finally, a nonnegative matrix factorization based algorithm is introduced to merge those very similar temporal complexes across different time points.
conclusionsExtensive experimental results demonstrate the proposed method is very effective in detecting temporal protein complexes than the state-of-the-art complex detection techniques.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.