ArticleFrontiers in genetics2021
Unearthing of Key Genes Driving the Pathogenesis of Alzheimer's Disease via Bioinformatics.
Article in Frontiers in genetics, 2021. 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
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
12 citing papers in PubMed, 21 citations in OpenAlex.
- Unravelling Synaptic and Metabolic Mechanisms of Cognitive Resilience in Asymptomatic Alzheimer's Disease Across Two Alzheimer's Disease Cohorts.Cellular and molecular neurobiology · 2026Article
- Cell- and sex-specificity in the transcriptomic response of the hippocampal neurovascular unit to obesity.Communications biology · 2025Article
- Advancing Alzheimer's Therapy: Computational strategies and treatment innovations.IBRO neuroscience reports · 2025Review
- Identification of UBE2N as a biomarker of Alzheimer's disease by combining WGCNA with machine learning algorithms.Scientific reports · 2025Article
- Mechanistic insights into connexin-mediated neuroglia crosstalk in neurodegenerative diseases.Frontiers in cellular neuroscience · 2025Review
- Identifying Hub Genes and miRNAs Associated with Alzheimer's Disease: A Bioinformatics Pathway to Novel Therapeutic Strategies.Biomolecules · 2024Article
- Article
- Cerebellum in Alzheimer's disease and other neurodegenerative diseases: an emerging research frontier.MedComm · 2024Review
- Exploiting machine learning models to identify novel Alzheimer's disease biomarkers and potential targets.Scientific reports · 2023Review
- Article
- Hereditable variants of classical protein tyrosine phosphatase genes: Will they prove innocent or guilty?Frontiers in cell and developmental biology · 2022Review
- Biological Significance of the Protein Changes Occurring in the Cerebrospinal Fluid of Alzheimer's Disease Patients: Getting Clues from Proteomic Studies.Diagnostics (Basel, Switzerland) · 2021Review
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 at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Alzheimer's disease (AD) is a neurodegenerative disease with unelucidated molecular pathogenesis. Herein, we aimed to identify potential hub genes governing the pathogenesis of AD. The AD datasets of GSE118553 and GSE131617 were collected from the NCBI GEO database. The weighted gene coexpression network analysis (WGCNA), differential gene expression analysis, and functional enrichment analysis were performed to reveal the hub genes and verify their role in AD. Hub genes were validated by machine learning algorithms. We identified modules and their corresponding hub genes from the temporal cortex (TC), frontal cortex (FC), entorhinal cortex (EC), and cerebellum (CE). We obtained 33, 42, 42, and 41 hub genes in modules associated with AD in TC, FC, EC, and CE tissues, respectively. Significant differences were recorded in the expression levels of hub genes between AD and the control group in the TC and EC tissues (
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.