1.
Chen, N, Zhou, M, Dong, X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395:507-513.
Google Scholar |
Crossref |
Medline2.
Shereen, MA, Khan, S, Kazmi, A, Bashir, N, Siddique, R. COVID-19 infection: origin, transmission, and characteristics of human coronaviruses. J Adv Res. 2020;24:91-98. doi:
10.1016/j.jare.2020.03.005. Google Scholar |
Crossref |
Medline3.
Ge, X-Y, Li, J-L, Yang, X-L, et al. Isolation and characterization of a bat SARS-like coronavirus that uses the ACE2 receptor. Nature. 2013;503:535-538.
Google Scholar |
Crossref |
Medline |
ISI4.
Jartti, T, Jartti, L, Ruuskanen, O, Söderlund-Venermo, M. New respiratory viral infections. Curr Opin Pulm Med. 2012;18:271-278.
Google Scholar |
Crossref |
Medline |
ISI5.
Chan, PK, Chan, MC. Tracing the SARS-coronavirus. J Thorac Dis. 2013;5:S118.
Google Scholar6.
Vijaykrishna, D, Smith, GJ, Zhang, JX, Peiris, J, Chen, H, Guan, Y. Evolutionary insights into the ecology of coronaviruses. J Virol. 2007;81:4012-4020.
Google Scholar |
Crossref |
Medline |
ISI7.
Desforges, M, Le Coupanec, A, Dubeau, P, et al. Human coronaviruses and other respiratory viruses: underestimated opportunistic pathogens of the central nervous system? Viruses. 2020;12:14.
Google Scholar |
Crossref8.
Chan-Yeung, M, Xu, RH. SARS: epidemiology. Respirology. 2003;8:S9-S14.
Google Scholar |
Crossref9.
http://www.emro.who.int/pandemic-epidemic-diseases/mers-cov/mers-situation-update-january-2020.html.
Google Scholar10.
Chan, JF-W, Yuan, S, Kok, K-H, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395:514-523.
Google Scholar |
Crossref |
Medline11.
Belser, JA, Rota, PA, Tumpey, TM. Ocular tropism of respiratory viruses. Microbiol Mol Biol Rev. 2013;77:144-156. doi:
10.1128/MMBR.00058-12. Google Scholar |
Crossref |
Medline12.
Lan, J, Ge, J, Yu, J, et al. Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor. Nature. 2020;581:215-220.
Google Scholar |
Crossref |
Medline13.
Paraskevis, D, Kostaki, EG, Magiorkinis, G, Panayiotakopoulos, G, Sourvinos, G, Tsiodras, S. Full-genome evolutionary analysis of the novel corona virus (2019-nCoV) rejects the hypothesis of emergence as a result of a recent recombination event. Infect Genet Evol. 2020;79:104212.
Google Scholar |
Crossref |
Medline14.
Qi, F, Qian, S, Zhang, S, Zhang, Z. Single cell RNA sequencing of 13 human tissues identify cell types and receptors of human coronaviruses. Biochem Biophys Res Commun. 2020;526:135-140.
Google Scholar |
Crossref |
Medline15.
Hoffmann, M, Kleine-Weber, H, Schroeder, S, et al. SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor. Cell. 2020;181:271-280.
Google Scholar |
Crossref |
Medline16.
Su, C . Bioinformatics: A Practical Guide to the Analysis of Genes & Proteins. Baxevanis, AD, Ouellette, BFF, eds. 3rd ed. Oxford: Oxford University Press. (original work published 2004); 2006.
Google Scholar17.
Bah, SY, Morang’a, CM, Kengne-Ouafo, JA, Amenga-Etego, L, Awandare, GA. Highlights on the application of genomics and bioinformatics in the fight against infectious diseases: challenges and opportunities in Africa. Front Genet. 2018;9:575.
Google Scholar |
Crossref |
Medline18.
Ray, M, Sable, MN, Sarkar, S, Hallur, VK. Essential interpretations of bioinformatics in COVID-19 pandemic. Meta Gene. 2021;27:100844.
Google Scholar |
Crossref |
Medline19.
Bayat, A. Science, medicine, and the future: bioinformatics. BMJ. 2002;324:1018.
Google Scholar |
Crossref |
Medline20.
Thusberg, J, Vihinen, M. Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods. Hum Mutat. 2009;30:703-714.
Google Scholar |
Crossref |
Medline21.
Li, L-P, Wang, Y-B, You, Z-H, Li, Y, An, J-Y. PCLPred: a bioinformatics method for predicting protein–protein interactions by combining relevance vector machine model with low-rank matrix approximation. Int J Mol Sci. 2018;19:1029.
Google Scholar |
Crossref22.
Yang, S, Fu, C, Lian, X, Dong, X, Zhang, Z. Understanding human-virus protein-protein interactions using a human protein complex-based analysis framework. mSystems. 2019;4:e00303-18. doi:
10.1128/mSystems.00303-18. Google Scholar |
Crossref23.
Gasteiger, E, Gattiker, A, Hoogland, C, Ivanyi, I, Appel, RD, Bairoch, A. ExPASy: the proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res. 2003;31:3784-3788. doi:
10.1093/nar/gkg563. Google Scholar |
Crossref |
Medline |
ISI24.
Szklarczyk, D, Gable, AL, Lyon, D, et al. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47:D607-D613. doi:
10.1093/nar/gky1131. Google Scholar |
Crossref25.
Slenter, DN, Kutmon, M, Hanspers, K, et al. WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research. Nucleic Acids Res.2018;46:D661-D667. doi:
10.1093/nar/gkx1064. Google Scholar |
Crossref |
Medline26.
Ge, SX, Jung, D, Yao, R. ShinyGO: a graphical gene-set enrichment tool for animals and plants. Bioinformatics. 2020;36:2628-2629. doi:
10.1093/bioinformatics/btz931. Google Scholar |
Crossref |
Medline27.
Consortium, GT. The genotype-tissue expression (GTEx) project. Nat Genet. 2013;45:580-585. doi:
10.1038/ng.2653. Google Scholar |
Crossref |
Medline28.
Yang, S, Kim, CY, Hwang, S, et al. COEXPEDIA: exploring biomedical hypotheses via co-expressions associated with medical subject headings (MeSH). Nucleic Acids Res. 2017;45:D389-D396. doi:
10.1093/nar/gkw868. Google Scholar |
Crossref29.
Zhu, Q, Wong, AK, Krishnan, A, et al. Targeted exploration and analysis of large cross-platform human transcriptomic compendia. Nat Methods. 2015;12:211-214. doi:
10.1038/nmeth.3249. Google Scholar |
Crossref |
Medline |
ISI30.
Barrett, T, Beck, J, Benson, DA, et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 2015;43:D6-D17. doi:
10.1093/nar/gku1130. Google Scholar |
Crossref |
Medline31.
Apweiler, R, Bairoch, A, Wu, CH, et al. UniProt: the Universal Protein knowledgebase. Nucleic Acids Res. 2004;32:D115-D119. doi:
10.1093/nar/gkh131. Google Scholar |
Crossref32.
Hunt, SE, McLaren, W, Gil, L, et al. Ensembl variation resources. Database. 2018;2018:bay119. doi:
10.1093/database/bay119. Google Scholar |
Crossref |
Medline33.
Lek, M, Karczewski, KJ, Minikel, EV, et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536:285-291. doi:
10.1038/nature19057. Google Scholar |
Crossref |
Medline |
ISI34.
Goodsell, DS, Zardecki, C, Di Costanzo, L, et al. RCSB Protein Data Bank: enabling biomedical research and drug discovery. Protein Sci. 2020;29:52-65.
Google Scholar |
Crossref |
Medline35.
Wilson, S, Greer, B, Hooper, J, et al. The membrane-anchored serine protease, TMPRSS2, activates PAR-2 in prostate cancer cells. Biochemical J. 2005;388:967-972.
Google Scholar |
Crossref |
Medline36.
Dahms, SO, Arciniega, M, Steinmetzer, T, Huber, R, Than, ME. Structure of the unliganded form of the proprotein convertase furin suggests activation by a substrate-induced mechanism. Proc Natl Acad Sci USA. 2016;113:11196-11201.
Google Scholar |
Crossref |
Medline37.
Henrich, S, Cameron, A, Bourenkov, G. P., et al. The crystal structure of the proprotein processing proteinase furin explains its stringent specificity. Nat Struct Biol. 2003;10:520-526.
Google Scholar |
Crossref |
Medline38.
Madden, TL, Schäffer, AA, Zhang, J, Zheng, Z, Miller, W, Lipman, DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Mol Biol Evol. 1997;25:3389-3402.
Google Scholar39.
Kumar, S, Stecher, G, Tamura, K. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol. 2016;33:1870-1874.
Google Scholar |
Crossref |
Medline |
ISI40.
Zhao, WM, Song, SH, Chen, ML, et al. The 2019 novel coronavirus resource. Yi Chuan. 2020;42:212-221. doi:
10.16288/j.yczz.20-030. Google Scholar |
Crossref |
Medline41.
Rice, P, Longden, L, Bleasby, A. EMBOSS: the European Molecular Biology Open Software suite. Trends Genet. 2000;16:276-277.
Google Scholar |
Crossref |
Medline |
ISI42.
Waterhouse, A, Bertoni, M, Bienert, S, et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 2018;46:W296-W303. doi:
10.1093/nar/gky427. Google Scholar |
Crossref |
Medline43.
Guex, N, Peitsch, MC, Schwede, T. Automated comparative protein structure modeling with SWISS-MODEL and Swiss-PdbViewer: a historical perspective. Electrophoresis. 2009;30:S162-173.
Google Scholar |
Crossref |
Medline44.
Xue, LC, Rodrigues, JP, Kastritis, PL, Bonvin, AM, Vangone, A. PRODIGY: a web server for predicting the binding affinity of protein-protein complexes. Bioinformatics. 2016;32:3676-3678. doi:
10.1093/bioinformatics/btw514. Google Scholar |
Crossref |
Medline45.
Sali, A, Blundell, T. Comparative modelling by satisfaction of spatial restraints. J Mol Biol. 1994;234:779-815.
Google Scholar |
Crossref46.
Sheik, SS, Sundararajan, P, Hussain, ASZ, Sekar, K. Ramachandran Plot on the web. Bioinformatics. 2002;18:1548-1549.
Google Scholar |
Crossref |
Medline47.
Dominguez, C, Boelens, R, Bonvin, AMJJ. HADDOCK: a protein-protein docking approach based on biochemical or biophysical information. J Am Chem Soc. 2003;125:1731-1737.
Google Scholar |
Crossref |
Medline48.
Hoffmann, M, Kleine-Weber, H, Pohlmann, S. A multibasic cleavage site in the spike protein of SARS-CoV-2 is essential for infection of human lung cells. Mol Cell. 2020;78:779e5-7784. doi:
10.1016/j.molcel.2020.04.022. Google Scholar |
Crossref |
Medline49.
Kim, H, Joe, A, Lee, M, et al. A genome-scale co-functional network of Xanthomonas genes can accurately reconstruct regulatory circuits controlled by two-component signaling systems. Mol Cells. 2019;42:166-174. doi:
10.14348/molcells.2018.0403. Google Scholar |
Crossref |
Medline50.
Hoffmann, M, Kleine-Weber, H, Pöhlmann, S. A multibasic cleavage site in the spike protein of SARS-CoV-2 is essential for infection of human lung cells. Mol Cell. 2020;78:779e5-7784.
Google Scholar |
Crossref |
Medline51.
Fadini, G, Morieri, M, Longato, E, Avogaro, A. Prevalence and impact of diabetes among people infected with SARS-CoV-2
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