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      The Omic Insights on Unfolding Saga of COVID-19

      review-article
      1 , 2 , 3 , 4 , 2 , 5 , 2 , 5 , 2 , 5 , 6 , 5 , 1 , 6 , 2 , 7 , 6 , 8 , 9 , 1 , 2 , 10 , 11 , 5 , 2 , 12 , 6 , 13 , 14 , , 2 , 15 , 16 , , 2 , 6 , , 2 , 5 , 17 ,
      Frontiers in Immunology
      Frontiers Media S.A.
      SARS-CoV-2, COVID-19, ORFs, machine learning, co-morbidities

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          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.

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          Most cited references208

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            A pneumonia outbreak associated with a new coronavirus of probable bat origin

            Since the outbreak of severe acute respiratory syndrome (SARS) 18 years ago, a large number of SARS-related coronaviruses (SARSr-CoVs) have been discovered in their natural reservoir host, bats 1–4 . Previous studies have shown that some bat SARSr-CoVs have the potential to infect humans 5–7 . Here we report the identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China. The epidemic, which started on 12 December 2019, had caused 2,794 laboratory-confirmed infections including 80 deaths by 26 January 2020. Full-length genome sequences were obtained from five patients at an early stage of the outbreak. The sequences are almost identical and share 79.6% sequence identity to SARS-CoV. Furthermore, we show that 2019-nCoV is 96% identical at the whole-genome level to a bat coronavirus. Pairwise protein sequence analysis of seven conserved non-structural proteins domains show that this virus belongs to the species of SARSr-CoV. In addition, 2019-nCoV virus isolated from the bronchoalveolar lavage fluid of a critically ill patient could be neutralized by sera from several patients. Notably, we confirmed that 2019-nCoV uses the same cell entry receptor—angiotensin converting enzyme II (ACE2)—as SARS-CoV.
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              A new coronavirus associated with human respiratory disease in China

              Emerging infectious diseases, such as severe acute respiratory syndrome (SARS) and Zika virus disease, present a major threat to public health 1–3 . Despite intense research efforts, how, when and where new diseases appear are still a source of considerable uncertainty. A severe respiratory disease was recently reported in Wuhan, Hubei province, China. As of 25 January 2020, at least 1,975 cases had been reported since the first patient was hospitalized on 12 December 2019. Epidemiological investigations have suggested that the outbreak was associated with a seafood market in Wuhan. Here we study a single patient who was a worker at the market and who was admitted to the Central Hospital of Wuhan on 26 December 2019 while experiencing a severe respiratory syndrome that included fever, dizziness and a cough. Metagenomic RNA sequencing 4 of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae, which is designated here ‘WH-Human 1’ coronavirus (and has also been referred to as ‘2019-nCoV’). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) that had previously been found in bats in China 5 . This outbreak highlights the ongoing ability of viral spill-over from animals to cause severe disease in humans.
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                20 October 2021
                2021
                20 October 2021
                : 12
                : 724914
                Affiliations
                [1] 1 Department of Bioinformatics, Hans Raj Mahila Maha Vidyalaya , Punjab, India
                [2] 2 Bioclues.org , Hyderabad, India
                [3] 3 Centre for Bioinformatics, School of Life Sciences, Pondicherry University , Puducherry, India
                [4] 4 Department of Biological Sciences, Indian Institute of Science Education and Research , Kolkata, India
                [5] 5 Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research , Jaipur, India
                [6] 6 Vignan’s Foundation for Science, Technology & Research (Deemed to be University) , Guntur, India
                [7] 7 Department of Chemistry, School of Basic Sciences, Manipal University Jaipur , Jaipur, India
                [8] 8 Functional Genomics Unit, Council of Scientific and Industrial Research- Institute of Genomics & Integrative Biology (CSIR-IGIB) , Delhi, India
                [9] 9 Department of Biotechnology, Haldia Institute of Technology , West Bengal, India
                [10] 10 Department of Microbiology, All India Institute of Medical Sciences, Bibinagar , Hyderabad, India
                [11] 11 Genomix CARL Pvt. Ltd , Pulivendula, India
                [12] 12 Department of Computer Science, Flame University , Pune, India
                [13] 13 Cytogenetics Laboratory, Department of Zoology, Benaras Hindu University , Varanasi, India
                [14] 14 Department of Genetics, University of Alabama , Birmingham, AL, United States
                [15] 15 German Cancer Research Centre (DKFZ) , Heidelberg, Germany
                [16] 16 Department of Applied Biology, Council of Scientific and Industrial Research-Indian Institute of Chemical Technology (CSIR-IICT) , Hyderabad, India
                [17] 17 Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham , Kerala, India
                Author notes

                Edited by: Betsy J. Barnes, Feinstein Institute for Medical Research, United States

                Reviewed by: Wanpen Chaicumpa, Mahidol University, Thailand; Siavash Bolourani, Feinstein Institute for Medical Research, United States

                *Correspondence: Prashanth Suravajhala, prash@ 123456bioclues.org ; Polavarapu Bilhan Kavi Kishor, pbkavi@ 123456yahoo.com ; Keshav K. Singh, kksingh@ 123456uab.edu ; Obul Reddy Bandapalli, bandapalli@ 123456gmail.com ;

                This article was submitted to Viral Immunology, a section of the journal Frontiers in Immunology

                †These authors have contributed equally to this work

                Article
                10.3389/fimmu.2021.724914
                8564481
                4a28cfa5-7b87-4f58-9faf-4f2a25c4bdf8
                Copyright © 2021 Kaur, Chopra, Bhushan, Gupta, Kumari P, Sivagurunathan, Shukla, Rajagopal, Bhalothia, Sharma, Naravula, Suravajhala, Gupta, Abbasi, Goswami, Singh, Narang, Polavarapu, Medicherla, Valadi, Kumar S, Chaubey, Singh, Bandapalli, Kavi Kishor and Suravajhala

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 14 June 2021
                : 27 September 2021
                Page count
                Figures: 2, Tables: 3, Equations: 0, References: 209, Pages: 17, Words: 8117
                Categories
                Immunology
                Review

                Immunology
                sars-cov-2,covid-19,orfs,machine learning,co-morbidities
                Immunology
                sars-cov-2, covid-19, orfs, machine learning, co-morbidities

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