ArticleBMC systems biology2010
Dynamic functional modules in co-expressed protein interaction networks of dilated cardiomyopathy.
Article in BMC systems biology, 2010. 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, 44 citations in OpenAlex.
- 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
- Temporal network analysis in systems biology: concepts, inference, and validation.Frontiers in bioinformatics · 2026Review
- Robust, scalable, and informative clustering for diverse biological networks.Genome biology · 2023Article
- Phenotype-tissue expression and exploration (PTEE) resource facilitates the choice of tissue for RNA-seq-based clinical genetics studies.BMC genomics · 2021Article
- Multi-omics approaches for revealing the complexity of cardiovascular disease.Briefings in bioinformatics · 2021Review
- Characterization of the Survival Influential Genes in Carcinogenesis.International journal of molecular sciences · 2021Article
- Investigation of the Genome-Wide Genetic and Epigenetic Networks for Drug Discovery Based on Systems Biology Approaches in Colorectal Cancer.Frontiers in genetics · 2020Article
- Differential network analysis and protein-protein interaction study reveals active protein modules in glucocorticoid resistance for infant acute lymphoblastic leukemia.Molecular medicine (Cambridge, Mass.) · 2019Article
- Analyzing gene expression profiles in dilated cardiomyopathy via bioinformatics methods.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2016Article
- A method for predicting protein complex in dynamic PPI networks.BMC bioinformatics · 2016Article
- A new strategy for exploring the hierarchical structure of cancers by adaptively partitioning functional modules from gene expression network.Scientific reports · 2016Article
- Article
- Fundamentals of protein interaction network mapping.Molecular systems biology · 2015Review
- Regulation rewiring analysis reveals mutual regulation between STAT1 and miR-155-5p in tumor immunosurveillance in seven major cancers.Scientific reports · 2015Article
- Decoding the complex genetic causes of heart diseases using systems biology.Biophysical reviews · 2015Article
- Pathway mapping and development of disease-specific biomarkers: protein-based network biomarkers.Journal of cellular and molecular medicine · 2015Review
- The discovery of integrated gene networks for autism and related disorders.Genome research · 2015Article
- Transcription factor networks in Drosophila melanogaster.Cell reports · 2014Article
- Dynamic modularity of host protein interaction networks in Salmonella Typhi infection.PloS one · 2014Article
- Topology of molecular interaction networks.BMC systems biology · 2013Review
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMolecular networks represent the backbone of molecular activity within cells and provide opportunities for understanding the mechanism of diseases. While protein-protein interaction data constitute static network maps, integration of condition-specific co-expression information provides clues to the dynamic features of these networks. Dilated cardiomyopathy is a leading cause of heart failure. Although previous studies have identified putative biomarkers or therapeutic targets for heart failure, the underlying molecular mechanism of dilated cardiomyopathy remains unclear.
resultsWe developed a network-based comparative analysis approach that integrates protein-protein interactions with gene expression profiles and biological function annotations to reveal dynamic functional modules under different biological states. We found that hub proteins in condition-specific co-expressed protein interaction networks tended to be differentially expressed between biological states. Applying this method to a cohort of heart failure patients, we identified two functional modules that significantly emerged from the interaction networks. The dynamics of these modules between normal and disease states further suggest a potential molecular model of dilated cardiomyopathy.
conclusionsWe propose a novel framework to analyze the interaction networks in different biological states. It successfully reveals network modules closely related to heart failure; more importantly, these network dynamics provide new insights into the cause of dilated cardiomyopathy. The revealed molecular modules might be used as potential drug targets and provide new directions for heart failure therapy.
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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.