ArticleGenes2022
A Novel 3-Gene Signature for Identifying COVID-19 Patients Based on Bioinformatics and Machine Learning.
Article in Genes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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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
17 citing papers in PubMed, 22 citations in OpenAlex.
- Comparative review of artificial intelligence for transcriptomic biomarker discovery in coronavirus disease 2019 (COVID-19).Briefings in bioinformatics · 2026Review
- A Unique Patient Stratification Method Combined with a Machine Learning Approach Identifies Novel Genetic Susceptibility and Protective Factors for Severe COVID-19 in a Hungarian Population.International journal of molecular sciences · 2026Article
- Predicting factors associated with anxiety by patients undergoing treatment for infectious diseases using a random-forest machine learning approach.Scientific reports · 2025Article
- Therapeutic Targets for Sepsis: Multicenter Proteome-Wide Analyses and Experimental Validation.Journal of proteome research · 2025Article
- The Strong Activation of p53 Tumor Suppressor Drives the Synthesis of the Enigmatic Isoform of DUSP13 Protein.Biomedicines · 2024Article
- AITeQ: a machine learning framework for Alzheimer's prediction using a distinctive five-gene signature.Briefings in bioinformatics · 2024Article
- Immune Characteristic Genes and Neutrophil Immune Transformation Studies in Severe COVID-19.Microorganisms · 2024Article
- Identification of an immune-related eRNA prognostic signature for clear cell renal cell carcinoma.Aging · 2024Article
- Identification of immune-related gene signature for predicting prognosis in uterine corpus endometrial carcinoma.Scientific reports · 2023Article
- A novel machine learning model based on ubiquitin-related gene pairs and clinical features to predict prognosis and treatment effect in colon adenocarcinoma.European journal of medical research · 2023Article
- Prognostic costimulatory molecule-related signature risk model correlates with immunotherapy response in colon cancer.Scientific reports · 2023Article
- Development of a novel immune infiltration-related diagnostic model for Alzheimer's disease using bioinformatic strategies.Frontiers in immunology · 2023Article
- Integration analysis of single-cell and spatial transcriptomics reveal the cellular heterogeneity landscape in glioblastoma and establish a polygenic risk model.Frontiers in oncology · 2023Article
- Identification and validation of a risk model and molecular subtypes based on tryptophan metabolism-related genes to predict the clinical prognosis and tumor immune microenvironment in lower-grade glioma.Frontiers in cellular neuroscience · 2023Article
- Identification and validation of neurotrophic factor-related gene signatures in glioblastoma and Parkinson's disease.Frontiers in immunology · 2023Article
- A novel Cuprotosis-related signature predicts the prognosis and selects personal treatments for melanoma based on bioinformatics analysis.Frontiers in oncology · 2023Article
- Construction and experimental validation of a B cell senescence-related gene signature to evaluate prognosis and immunotherapeutic sensitivity in bladder cancer.Functional & integrative genomics · 2022Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although many biomarkers associated with coronavirus disease 2019 (COVID-19) were found, a novel signature relevant to immune cells has not been developed. In this work, the "CIBERSORT" algorithm was used to assess the fraction of immune infiltrating cells in GSE152641 and GSE171110. Key modules associated with important immune cells were selected by the "WGCNA" package. The "GO" enrichment analysis was used to reveal the biological function associated with COVID-19. The "Boruta" algorithm was used to screen candidate genes, and the "LASSO" algorithm was used for collinearity reduction. A novel gene signature was developed based on multivariate logistic regression analysis. Subsequently, M0 macrophages (PR
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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.