Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 infections to idiopathic pulmonary fibrosis and chronic obstructive pulmonary disease patients.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33847347", "kind": "science-record", "revision": 4, "content_hash": "sha256:5d03703f8a735bf3186dd944baac1b6fc823972353bde91a4291f6b6e0b0f14d", "created_at": "2026-11-01T17:35:05Z", "updated_at": "2026-11-01T22:03:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 infections to idiopathic pulmonary fibrosis and chronic obstructive pulmonary disease patients.", "doi": "10.1093/bib/bbab115", "pmid": "33847347", "authors": ["S M Hasan Mahmud", "Md Al-Mustanjid", "Farzana Akter", "Md Shazzadur Rahman", "Kawsar Ahmed", "Md Habibur Rahman", "Wenyu Chen", "Mohammad Ali Moni"], "journal": "Briefings in bioinformatics", "year": 2021, "abstract": "The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), better known as COVID-19, has become a current threat to humanity. The second wave of the SARS-CoV-2 virus has hit many countries, and the confirmed COVID-19 cases are quickly spreading. Therefore, the epidemic is still passing the terrible stage. Having idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD) are the risk factors of the COVID-19, but the molecular mechanisms that underlie IPF, COPD, and CVOID-19 are not well understood. Therefore, we implemented transcriptomic analysis to detect common pathways and molecular biomarkers in IPF, COPD, and COVID-19 that help understand the linkage of SARS-CoV-2 to the IPF and COPD patients. Here, three RNA-seq datasets (GSE147507, GSE52463, and GSE57148) from Gene Expression Omnibus (GEO) is employed to detect mutual differentially expressed genes (DEGs) for IPF, and COPD patients with the COVID-19 infection for finding shared pathways and candidate drugs. A total of 65 common DEGs among these three datasets were identified. Various combinatorial statistical methods and bioinformatics tools were used to build the protein-protein interaction (PPI) and then identified Hub genes and essential modules from this PPI network. Moreover, we performed functional analysis under ontologies terms and pathway analysis and found that IPF and COPD have some shared links to the progression of COVID-19 infection. Transcription factors-genes interaction, protein-drug interactions, and DEGs-miRNAs coregulatory network with common DEGs also identified on the datasets. We think that the candidate drugs obtained by this study might be helpful for effective therapeutic in COVID-19.", "claims": [{"id": "claim-method", "statement": "Therefore, we implemented transcriptomic analysis to detect common pathways and molecular biomarkers in IPF, COPD, and COVID-19 that help understand the linkage of SARS-CoV-2 to the IPF and COPD patients.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33847347", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Therefore, we implemented transcriptomic analysis to detect common pathways and molecular biomarkers in IPF, COPD, and COVID-19 that help understand the linkage of SARS-CoV-2 to the IPF and COPD patients."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Here, three RNA-seq datasets (GSE147507, GSE52463, and GSE57148) from Gene Expression Omnibus (GEO) is employed to detect mutual differentially expressed genes (DEGs) for IPF, and COPD patients with the COVID-19 infection for finding shared pathways and candidate drugs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33847347", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Here, three RNA-seq datasets (GSE147507, GSE52463, and GSE57148) from Gene Expression Omnibus (GEO) is employed to detect mutual differentially expressed genes (DEGs) for IPF, and COPD patients with the COVID-19 infection for finding shared pathways and candidate drugs."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A total of 65 common DEGs among these three datasets were identified.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:33847347", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "A total of 65 common DEGs among these three datasets were identified."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A total of 65 common DEGs among these three datasets were identified.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:33847347"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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