ArticleResearch (Washington, D.C.)2024
Uncovering the Pre-Deterioration State during Disease Progression Based on Sample-Specific Causality Network Entropy (SCNE).
Article in Research (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Self-supervised reservoir computing with spatial-temporal encoding for identifying critical transitions.Nature communications · 2026Article
- Kynurenine promotes angiogenesis through mTOR signaling in head and neck squamous cell carcinoma.Scientific reports · 2026Article
- Hallmarks of the pre-disease state: prevention and control of the pre-disease state, a tipping point between health and disease.Cell discovery · 2026Article
- Utilizing Causal Network Markers to Identify Tipping Points ahead of Critical Transition.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- TransMarker: Unveiling dynamic network biomarkers in cancer progression through cross-state graph alignment and optimal transport.PLoS computational biology · 2025Article
- sPGGM: a sample-perturbed Gaussian graphical model for identifying pre-disease stages and signaling molecules of disease progression.National science review · 2025Article
- Dynamic network entropy for pinpointing the pre-outbreak stage of infectious disease.Journal of the Royal Society, Interface · 2025Article
- DNFE: Directed network flow entropy for detecting tipping points during biological processes.PLoS computational biology · 2025Article
- Ultralow-Dimensionality Reduction for Identifying Critical Transitions by Spatial-Temporal PCA.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- "Weibing" in traditional Chinese medicine-biological basis and mathematical representation of disease-susceptible state.Acta pharmaceutica Sinica. B · 2025Review
- Uncovering critical transitions and molecule mechanisms in disease progressions using Gaussian graphical optimal transport.Communications biology · 2025Article
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- General relationship of local topologies, global dynamics, and bifurcation in cellular networks.NPJ systems biology and applications · 2024Article
- Enhancer-driven gene regulatory networks inference from single-cell RNA-seq and ATAC-seq data.Briefings in bioinformatics · 2024Article
- eMCI: An Explainable Multimodal Correlation Integration Model for Unveiling Spatial Transcriptomics and Intercellular Signaling.Research (Washington, D.C.) · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Complex diseases do not always follow gradual progressions. Instead, they may experience sudden shifts known as critical states or tipping points, where a marked qualitative change occurs. Detecting such a pivotal transition or pre-deterioration state holds paramount importance due to its association with severe disease deterioration. Nevertheless, the task of pinpointing the pre-deterioration state for complex diseases remains an obstacle, especially in scenarios involving high-dimensional data with limited samples, where conventional statistical methods frequently prove inadequate. In this study, we introduce an innovative quantitative approach termed sample-specific causality network entropy (SCNE), which infers a sample-specific causality network for each individual and effectively quantifies the dynamic alterations in causal relations among molecules, thereby capturing critical points or pre-deterioration states of complex diseases. We substantiated the accuracy and efficacy of our approach via numerical simulations and by examining various real-world datasets, including single-cell data of epithelial cell deterioration (EPCD) in colorectal cancer, influenza infection data, and three different tumor cases from The Cancer Genome Atlas (TCGA) repositories. Compared to other existing six single-sample methods, our proposed approach exhibits superior performance in identifying critical signals or pre-deterioration states. Additionally, the efficacy of computational findings is underscored by analyzing the functionality of signaling biomarkers.
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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.