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Publication Type : Journal Article
Publisher : Front Immunol
Source : Front Immunol. 2021 Oct 20;12:724914.
Keywords : COVID-19, ORFs, SARS-CoV-2, Co-morbidities, Machine Learning
Campus : Amritapuri
School : School of Biotechnology
Department : biotechnology
Year : 2021
Abstract : The year 2019 has seen an emergence of the novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease of 2019 (COVID-19). Since the onset of the pandemic, biological and interdisciplinary research is being carried out across the world at a rapid pace to beat the pandemic. There is an increased need to comprehensively understand various aspects of the virus from detection to treatment options including drugs and vaccines for effective global management of the disease. In this review, we summarize the salient findings pertaining to SARS-CoV-2 biology, including symptoms, hosts, epidemiology, SARS-CoV-2 genome, and its emerging variants, viral diagnostics, host-pathogen interactions, alternative antiviral strategies and application of machine learning heuristics and artificial intelligence for effective management of COVID-19 and future pandemics.
Cite this Research Publication : Kaur A, Chopra M, Bhushan M, Gupta S, Kumari P H, Sivagurunathan N, Shukla N, Rajagopal S, Bhalothia P, Sharma P, Naravula J, Suravajhala R, Gupta A, Abbasi BA, Goswami P, Singh H,
Narang R, Polavarapu R, Medicherla KM, Valadi J, Kumar S A, Chaubey G, Singh KK, Bandapalli OR, Kavi Kishor PB, Suravajhala P. The Omic Insights on Unfolding Saga of COVID-19. Front Immunol. 2021 Oct 20;12:724914. doi: 10.3389/fimmu.2021.724914. PMID: 34745097; PMCID: PMC8564481