ArticleBiomolecules2020
System-Based Differential Gene Network Analysis for Characterizing a Sample-Specific Subnetwork.
Article in Biomolecules, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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.
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Who cites it
12 citing papers in PubMed, 22 citations in OpenAlex.
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- Peripheral bloodStroke and vascular neurology · 2025Article
- Network analysis reveals causal relationships among individual background risk factors leading to influenza susceptibility.Scientific reports · 2025Article
- A Thorough Review of the Clinical Applications of Artificial Intelligence in Lung Cancer.Cancers · 2025Review
- Idiopathic pulmonary fibrosis-specific Bayesian network integrating extracellular vesicle proteome and clinical information.Scientific reports · 2024Article
- Inference of differential gene regulatory networks using boosted differential trees.Bioinformatics advances · 2024Article
- Whole blood transcriptome profiling identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis.Biochemistry and biophysics reports · 2022Article
- Novel cancer subtyping method based on patient-specific gene regulatory network.Scientific reports · 2021Article
- Dynamic changes in gene-to-gene regulatory networks in response to SARS-CoV-2 infection.Scientific reports · 2021Article
- Application of Artificial Intelligence for Medical Research.Biomolecules · 2021Article
- Interpreting Functional Impact of Genetic Variations by Network QTL for Genotype-Phenotype Association Study.Frontiers in cell and developmental biology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Gene network estimation is a method key to understanding a fundamental cellular system from high throughput omics data. However, the existing gene network analysis relies on having a sufficient number of samples and is required to handle a huge number of nodes and estimated edges, which remain difficult to interpret, especially in discovering the clinically relevant portions of the network. Here, we propose a novel method to extract a biomedically significant subnetwork using a Bayesian network, a type of unsupervised machine learning method that can be used as an explainable and interpretable artificial intelligence algorithm. Our method quantifies sample specific networks using our proposed
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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.