{"entity": "publication", "iuid": "b425a447d0f7479f9b5db768890b886b", "timestamp": "2026-06-17T07:06:48.282Z", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/b425a447d0f7479f9b5db768890b886b.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/b425a447d0f7479f9b5db768890b886b"}}, "title": "Identification of essential genes associated with SARS-CoV-2 infection as potential drug target candidates with machine learning algorithms.", "authors": [{"family": "Taheri", "given": "Golnaz", "initials": "G", "orcid": "0000-0002-2741-0355", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/014c217121d346b2b371bbc1c2fede57.json"}}, {"family": "Habibi", "given": "Mahnaz", "initials": "M", "orcid": "0000-0002-8969-2706", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/f04af4e059814b78bfb107c3a5782f70.json"}}], "type": "journal article", "published": "2023-09-13", "journal": {"title": "Sci Rep", "issn": "2045-2322", "issn-l": "2045-2322", "volume": "13", "issue": "1", "pages": "15141"}, "abstract": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires the fast discovery of effective treatments to fight this worldwide concern. Several genes associated with the SARS-CoV-2, which are essential for its functionality, pathogenesis, and survival, have been identified. These genes, which play crucial roles in SARS-CoV-2 infection, are considered potential therapeutic targets. Developing drugs against these essential genes to inhibit their regular functions could be a good approach for COVID-19 treatment. Artificial intelligence and machine learning methods provide powerful infrastructures for interpreting and understanding the available data and can assist in finding fast explanations and cures. We propose a method to highlight the essential genes that play crucial roles in SARS-CoV-2 pathogenesis. For this purpose, we define eleven informative topological and biological features for the biological and PPI networks constructed on gene sets that correspond to COVID-19. Then, we use three different unsupervised learning algorithms with different approaches to rank the important genes with respect to our defined informative features. Finally, we present a set of 18 important genes related to COVID-19. Materials and implementations are available at: https://github.com/MahnazHabibi/Gene_analysis .", "doi": "10.1038/s41598-023-42127-9", "pmid": "37704748", "labels": {"Golnaz Taheri": null, "DDLS Fellow": null}, "xrefs": [{"db": "pmc", "key": "PMC10499814"}, {"db": "pii", "key": "10.1038/s41598-023-42127-9"}], "notes": [], "created": "2025-03-21T09:08:32.053Z", "modified": "2025-03-21T10:34:27.036Z"}