ArticleInternational journal of genomics2014
Expression data analysis to identify biomarkers associated with asthma in children.
Article in International journal of genomics, 2014. 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
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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.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- E2F1-Activated lncRNA FTX Promotes Asthma Progression via Regulating the SRSF1/RBPJ Axis.Allergy, asthma & immunology research · 2026Article
- Bioinformatics analysis and preliminary validation of autophagy-related genes in asthma disease.Scientific reports · 2025Article
- Transcription Factor E2F1 Regulates the Expression of ADRB2.International journal of analytical chemistry · 2023Article
- Analysis of GWAS-nominated loci for lung cancer and COPD revealed a new asthma locus.BMC pulmonary medicine · 2022Article
- Aberrant Methylation of Aging-Related Genes in Asthma.Frontiers in molecular biosciences · 2021Article
- PELP1 Suppression Inhibits Gastric Cancer Through Downregulation of c-Src-PI3K-ERK Pathway.Frontiers in oncology · 2019Article
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Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Asthma is characterized by recurrent episodes of wheezing, shortness of breath, chest tightness, and coughing. It is usually caused by a combination of complex and incompletely understood environmental and genetic interactions. We obtained gene expression data with high-throughput screening and identified biomarkers of children's asthma using bioinformatics tools. Next, we explained the pathogenesis of children's asthma from the perspective of gene regulatory networks: DAVID was applied to perform Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enriching analysis for the top 3000 pairs of relationships in differentially regulatory network. Finally, we found that HAND1, PTK1, NFKB1, ZIC3, STAT6, E2F1, PELP1, USF2, and CBFB may play important roles in children's asthma initiation. On account of regulatory impact factor (RIF) score, HAND1, PTK7, and ZIC3 were the potential asthma-related factors. Our study provided some foundations of a strategy for biomarker discovery despite a poor understanding of the mechanisms underlying children's asthma.
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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.