ArticleScientific reports2015
Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis.
Article in Scientific reports, 2015. 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.
- QIGTD: identifying critical genes in the evolution of lung adenocarcinoma with tensor decomposition.BioData mining · 2024Article
- Gene expression ranking change based single sample pre-disease state detection.Frontiers in genetics · 2024Article
- Identification of Hub Genes With Differential Correlations in Sepsis.Frontiers in genetics · 2022Article
- Dynamic Host Immune and Transcriptomic Responses to Respiratory Syncytial Virus Infection in a Vaccination-Challenge Mouse Model.Virologica Sinica · 2021Article
- Identification of Key Genes With Differential Correlations in Lung Adenocarcinoma.Frontiers in cell and developmental biology · 2021Article
- scPADGRN: A preconditioned ADMM approach for reconstructing dynamic gene regulatory network using single-cell RNA sequencing data.PLoS computational biology · 2020Article
- Hepatitis B Virus Core Particles Containing a Conserved Region of the G Protein Combined with Interleukin-35 Protected Mice against Respiratory Syncytial Virus Infection without Vaccine-Enhanced Immunopathology.Journal of virology · 2020Article
- Transcriptomic Data Analyses Reveal a Reprogramed Lipid Metabolism in HCV-Derived Hepatocellular Cancer.Frontiers in cell and developmental biology · 2020Article
- Control of multilayer biological networks and applied to target identification of complex diseases.BMC bioinformatics · 2019Article
- Impulsive control of a nonlinear dynamical network and its application to biological networks.Journal of biological physics · 2019Article
- Identification of differentially expressed proteins in the injured lung from zinc chloride smoke inhalation based on proteomics analysis.Respiratory research · 2019Article
- Individual-specific edge-network analysis for disease prediction.Nucleic acids research · 2017Article
- Mathematical modeling and quantitative analysis of HIV-1 Gag trafficking and polymerization.PLoS computational biology · 2017Article
- A new two-stage method for revealing missing parts of edges in protein-protein interaction networks.PloS one · 2017Article
- Several Indicators of Critical Transitions for Complex Diseases Based on Stochastic Analysis.Computational and mathematical methods in medicine · 2017Article
- Inference of Biochemical S-Systems via Mixed-Variable Multiobjective Evolutionary Optimization.Computational and mathematical methods in medicine · 2017Article
- Correlation-based iterative clustering methods for time course data: The identification of temporal gene response modules for influenza infection in humans.Infectious Disease Modelling · 2016Article
- Using Multi-objective Optimization to Identify Dynamical Network Biomarkers as Early-warning Signals of Complex Diseases.Scientific reports · 2016Article
- Article
- Differential variability and correlation of gene expression identifies key genes involved in neuronal differentiation.BMC systems biology · 2015Article
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5 authors.
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Abstract
The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.
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