ReviewComputational and structural biotechnology journal2022
Development of a dynamic network biomarkers method and its application for detecting the tipping point of prior disease development.
Review in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Hourly Blood Urea Nitrogen Trajectories and ICU Mortality Risk in Critically Ill Patients with Gastrointestinal Bleeding: A Multicenter Retrospective Cohort Study.Advances in therapy · 2026Article
- Detection of pre-transition phases during biological development using single-sample network entropy (SNE).NPJ systems biology and applications · 2025Article
- RPL6 Interacts with HMGCS1 to Stabilize HIF-1α by Promoting Cholesterol Production in Hepatocellular Carcinoma.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Integrating Dynamical Systems Modeling with Spatiotemporal scRNA-Seq Data Analysis.Entropy (Basel, Switzerland) · 2025Review
- Identification of the Cellular Tipping Point in the Inflammation Model of LPS-Induced RAW264.7 Macrophages Through Raman Spectroscopy and the Dynamical Network Biomarker Theory.Molecules (Basel, Switzerland) · 2025Article
- Identifying the potential miRNA biomarkers based on multi-view networks and reinforcement learning for diseases.Briefings in bioinformatics · 2023Article
- MAPKAPK2, a potential dynamic network biomarker of α-synuclein prior to its aggregation in PD patients.NPJ Parkinson's disease · 2023Article
- Low expression of the dynamic network markers FOS/JUN in pre-deteriorated epithelial cells is associated with the progression of colorectal adenoma to carcinoma.Journal of translational medicine · 2023Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The dynamic network biomarker (DNB) method has advanced since it was first proposed. This review discusses advances in the DNB method that can identify the dynamic change in the expression signature related to the critical time point of disease progression by utilizing different kinds of transcriptome data. The DNB method is good at identifying potential biomarkers for cancer and other disease development processes that are represented by a limited molecular profile change between the normal and critical stages. We highlight that the cancer tipping point or premalignant state has been widely discovered for different types of cancer by using the DNB method that utilizes bulk or single-cell RNA sequencing data. This method could also be applied to other dynamic research studies and help identify early warning signals, such as the prediction of a pre-outbreak of COVID-19. We also discuss how the identification of reliable biomarkers of cancer and the development of new methods can be utilized for early detection and intervention and provide insights into emerging paths of the widespread biomarker candidate pool for further validation and disease/health management.
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Registered trials
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.