ArticleFrontiers in pharmacology2021
Identification of Novel Gene Signatures using Next-Generation Sequencing Data from COVID-19 Infection Models: Focus on Neuro-COVID and Potential Therapeutics.
Article in Frontiers in pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Unraveling the molecular mechanisms in severe Alzheimer's disease based on transcriptomic data using next generation knowledge discovery methods.Pakistan journal of medical sciences · 2026Article
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- Dysregulated Pathways During Pregnancy Predict Drug Candidates in Neurodevelopmental Disorders.Neuroscience bulletin · 2025Article
- A feasibility of computational drug screening for Fuchs endothelial corneal dystrophy.Scientific reports · 2025Article
- Identification of gene signatures and potential pharmaceutical candidates linked to COVID-19-related depression based on gene expression profiles.Frontiers in pharmacology · 2025Article
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- Deciphering aging-associated molecular mechanisms in bone marrow derived hematopoietic stem cells in the elderly using NGS data.Bioinformation · 2024Article
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- The Natural Products Withaferin A and Withanone from the Medicinal HerbJournal of natural products · 2022Article
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- Multi-Level Biological Network Analysis and Drug Repurposing Based on Leukocyte Transcriptomics in Severe COVID-19: In Silico Systems Biology to Precision Medicine.Journal of personalized medicine · 2022Article
- A path-based analysis of infected cell line and COVID-19 patient transcriptome reveals novel potential targets and drugs against SARS-CoV-2.Research square · 2022Article
- Decoding the Role of Astrocytes in the Entorhinal Cortex in Alzheimer's Disease Using High-Dimensional Single-Nucleus RNA Sequencing Data and Next-Generation Knowledge Discovery Methodologies: Focus on Drugs and Natural Product Remedies for Dementia.Frontiers in pharmacology · 2021Article
- Exploration of potential molecular mechanisms and genotoxicity of anti-cancer drugs using next generation knowledge discovery methods.Pakistan journal of medical sciencesArticle
Corrections and comments
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3 authors.
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Abstract
SARS-CoV-2 is the causative agent for coronavirus disease-19 (COVID-19) and belongs to the family Coronaviridae that causes sickness varying from the common cold to more severe illnesses such as severe acute respiratory syndrome, sudden stroke, neurological complications (Neuro-COVID), multiple organ failure, and mortality in some patients. The gene expression profiles of COVID-19 infection models can be used to decipher potential therapeutics for COVID-19 and related pathologies, such as Neuro-COVID. Here, we used the raw RNA-seq reads (Single-End) in quadruplicates derived using Illumina Next Seq 500 from SARS-CoV-infected primary human bronchial epithelium (NHBE) and mock-treated NHBE cells obtained from the Gene Expression Omnibus (GEO) (GSE147507), and the quality control (QC) was evaluated using the CLC Genomics Workbench 20.0 (Qiagen, United States) before the RNA-seq analysis using BioJupies web tool and iPathwayGuide for gene ontologies (GO), pathways, upstream regulator genes, small molecules, and natural products. Additionally, single-cell transcriptomics data (GSE163005) of meta clusters of immune cells from the cerebrospinal fluid (CSF), such as T-cells/natural killer cells (NK) (TcMeta), dendritic cells (DCMeta), and monocytes/granulocyte (monoMeta) cell types for comparison, namely, Neuro-COVID versus idiopathic intracranial hypertension (IIH), were analyzed using iPathwayGuide. L1000 fireworks display (L1000FWD) and L1000 characteristic direction signature search engine (L1000 CDS
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