ReviewGenes2023
Networks as Biomarkers: Uses and Purposes.
Review in Genes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Heavy Metal-Driven Oral Dysbiosis: Salivary Toxicometallomics at the Host-Microbiome Interface Across Pathologies.Life (Basel, Switzerland) · 2026Review
- Network analysis predicts pembrolizumab response in advanced NSCLC with PD-L1 < 50.Cancer cell international · 2026Article
- ASGR2 and CLEC12A as Prognostically Relevant C-Type Lectin Hubs in Glioblastoma.International journal of molecular sciences · 2026Article
- De Novo Transcriptome Assembly Reveals Insights Into Osmoregulation and Oxidative Stress Response in the Gills of the Southern King Crab (Ecology and evolution · 2025Article
- ProtLoc-GRPO: Cell line-specific subcellular localization prediction using a graph-based model and reinforcement learning.bioRxiv : the preprint server for biology · 2025Article
- Immunohistochemical Expression Levels of Epidermal Growth Factor Receptor, Cyclooxygenase-2, and Ki-67 in Canine Cutaneous Squamous Cell Carcinomas.Current issues in molecular biology · 2024Article
- Circuits and Biomarkers of the Central Nervous System Relating to Astronaut Performance: Summary Report for a NASA-Sponsored Technical Interchange Meeting.Life (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Networks-based approaches are often used to analyze gene expression data or protein-protein interactions but are not usually applied to study the relationships between different biomarkers. Given the clinical need for more comprehensive and integrative biomarkers that can help to identify personalized therapies, the integration of biomarkers of different natures is an emerging trend in the literature. Network analysis can be used to analyze the relationships between different features of a disease; nodes can be disease-related phenotypes, gene expression, mutational events, protein quantification, imaging-derived features and more. Since different biomarkers can exert causal effects between them, describing such interrelationships can be used to better understand the underlying mechanisms of complex diseases. Networks as biomarkers are not yet commonly used, despite being proven to lead to interesting results. Here, we discuss in which ways they have been used to provide novel insights into disease susceptibility, disease development and severity.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.