ArticleScientific reports2021
Dynamic changes in gene-to-gene regulatory networks in response to SARS-CoV-2 infection.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 13 citations in OpenAlex.
- Blood and skin carotenoid levels are inversely associated with the prevalence of periodontal diseases in populations with normal occlusion: a cross-sectional analysis from the Iwaki health promotion project.Nutrition journal · 2026Article
- Using Machine Learning to Identify Factors Affecting Antibody Production and Adverse Reactions After COVID-19 Vaccination.Vaccines · 2026Article
- Network analysis reveals causal relationships among individual background risk factors leading to influenza susceptibility.Scientific reports · 2025Article
- A python library for the fast and scalable computation of biologically meaningful individual specific networks.Scientific reports · 2024Article
- Gene network inference from single-cell omics data and domain knowledge for constructing COVID-19-specificFrontiers in genetics · 2023Article
- Identification of transcriptional regulatory network associated with response of host epithelial cells to SARS-CoV-2.Scientific reports · 2021Article
- Novel cancer subtyping method based on patient-specific gene regulatory network.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The current pandemic of SARS-CoV-2 has caused extensive damage to society. The characterization of SARS-CoV-2 profiles has been addressed by researchers globally with the aim of resolving this disruptive crisis. This investigation process is indispensable to understand how SARS-CoV-2 behaves in human host cells. However, little is known about the systematic molecular mechanisms involved in the effects of SARS-CoV-2 infection on human host cells. Here, we present gene-to-gene regulatory networks in response to SARS-CoV-2 using a Bayesian network. We examined the dynamic changes in the SARS-CoV-2-purturbated networks established by our proposed framework for gene network analysis, thus revealing that interferon signaling gradually switched to the subsequent inflammatory cytokine signaling cascades. Furthermore, we succeeded in capturing a COVID-19 patient-specific network in which transduction of these signals was concurrently induced. This enabled us to explore the local regulatory systems influenced by SARS-CoV-2 in host cells more precisely at an individual level. Our panel of network analyses has provided new insights into SARS-CoV-2 research from the perspective of cellular systems.
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