Pyrc K, Jebbink MF, Berkhout B, Van der Hoek L. Genome structure and transcriptional regulation of human coronavirus NL63. Virol J. 2004;1:1–11.
Liu DX, Liang JQ, Fung TS. Human coronavirus-229E,-OC43,-NL63, and-HKU1 (Coronaviridae). Encyclopedia of Virology. 2021;2:428–440.
Hamre D, Procknow JJ. A new virus isolated from the human respiratory tract. Proc Soc Exp Biol Med. 1966;121:190–3.
Article CAS PubMed Google Scholar
Folz RJ, Elkordy MA. Coronavirus pneumonia following autologous bone marrow transplantation for breast cancer. Chest. 1999;115:901–5.
Article CAS PubMed Google Scholar
Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, Zhao X, Huang B, Shi W, Lu R: China Novel Coronavirus Investigating and Research Team. China Novel Coronavirus, I., and Research, T. A Novel Coronavirus from Patients with Pneumonia in China. N Engl J Med. 2020;382:727-733.
Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, Zhao X, Huang B, Shi W, Lu R. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020.
Hageman JR. The coronavirus disease 2019 (COVID-19). NJ: SLACK Incorporated Thorofare; 2020.
WHO Africa. Over two thirds of Africans infected by COVID virus since pandemic began – WHO. Reuters. 2022. https://www.reuters.com/world/africa/over-two-thirds-africans-infected-by-covid-virus-since-pandemic-began-who-2022-04-07/. Accessed 7 Apr 2022.
Williams PC, Howard-Jones AR, Hsu P, Palasanthiran P, Gray PE, McMullan BJ, Britton PN, Bartlett AW. SARS-CoV-2 in children: spectrum of disease, transmission and immunopathological underpinnings. Pathology 2020.
Zaim S, Chong JH, Sankaranarayanan V, Harky A. COVID-19 and multiorgan response. Curr Probl Cardiol. 2020;45: 100618.
Article PubMed PubMed Central Google Scholar
Jones S, Thornton JM. Principles of protein-protein interactions. Proc Natl Acad Sci. 1996;93:13–20.
Article CAS PubMed PubMed Central Google Scholar
Teichmann SA, Murzin AG, Chothia C. Determination of protein function, evolution and interactions by structural genomics. Curr Opin Struct Biol. 2001;11:354–63.
Article CAS PubMed Google Scholar
Dehghan Z, Mirmotalebisohi SA, Sameni M, Bazgiri M, Zali H. A Motif-based network analysis of regulatory patterns in doxorubicin effects on treating breast cancer, a systems biology study. Avicenna J Med Biotechnol. 2022;14:137.
PubMed PubMed Central Google Scholar
Dehghan Z, Mohammadi-Yeganeh S, Sameni M, Mirmotalebisohi SA, Zali H, Salehi M. Repurposing new drug candidates and identifying crucial molecules underlying PCOS Pathogenesis Based On Bioinformatics Analysis. DARU J Pharm Sci. 2021;29:353–66.
Sameni M, Mirmotalebisohi SA, Dehghan Z, Abooshahab R, Khazaei-Poul Y, Mozafar M, Zali H. Deciphering molecular mechanisms of SARS-CoV-2 pathogenesis and drug repurposing through GRN motifs: a comprehensive systems biology study. 3 Biotech 2023;13:117.
Sameni M, Mirmotalebisohi SA, Dadashkhan S, Ghani S, Abbasi M, Noori E, Zali H. COVID-19: a novel holistic systems biology approach to predict its molecular mechanisms (in vitro) and repurpose drugs. DARU J Pharm Sci. 2023;31:155–71.
Saberi F, Dehghan Z, Noori E, Taheri Z, Sameni M, Zali H. Identification of critical molecular factors and side effects underlying the response to thalicthuberine in prostate cancer: a systems biology approach. Avicenna J Med Biotechnol. 2023;15:53.
PubMed PubMed Central Google Scholar
Saberi F, Dehghan Z, Noori E, Zali H. Identification of renal transplantation rejection biomarkers in blood using the systems biology approach. Iranian Biomed J. 2023;27:375–87.
Dadashkhan S, Mirmotalebisohi SA, Poursheykhi H, Sameni M, Ghani S, Abbasi M, Kalantari S, Zali H. Deciphering crucial genes in multiple sclerosis pathogenesis and drug repurposing: a systems biology approach. J Proteomics. 2023;280: 104890.
Article CAS PubMed Google Scholar
Khazaei-Poul Y, Mirmotalebisohi SA, Zali H, Molavi Z, Mohammadi-Yeganeh S. Identification of miR-3182 and miR-3143 target genes involved in the cell cycle as a novel approach in TNBC treatment: a systems biology approach. Chem Biol Drug Des. 2023;101:662–77.
Article CAS PubMed Google Scholar
Ghani S, Kalantari S, Mirmotalebisohi SA, Sameni M, Poursheykhi H, Dadashkhan S, Abbasi M, Zali H. Specific regulatory motifs network in SARS-CoV-2-infected Caco-2 cell line, as a model of gastrointestinal infections. Cell Reprogram. 2022;24:26–37.
Article CAS PubMed Google Scholar
Llabrés M, Valiente G. Alignment of virus-host protein-protein interaction networks by integer linear programming: SARS-CoV-2. PLoS ONE. 2020;15: e0236304.
Article PubMed PubMed Central Google Scholar
Chasman D, Walters KB, Lopes TJ, Eisfeld AJ, Kawaoka Y, Roy S. Integrating transcriptomic and proteomic data using predictive regulatory network models of host response to pathogens. PLoS Comput Biol. 2016;12: e1005013.
Article PubMed PubMed Central Google Scholar
Ochsner SA, Pillich RT, McKenna NJ. Consensus transcriptional regulatory networks of coronavirus-infected human cells. Sci Data. 2020;7:1–20.
Amemiya T, Horimoto K, Fukui K. Application of multiple omics and network projection analyses to drug repositioning for pathogenic mosquito-borne viruses. Sci Rep. 2021;11:1–13.
Gordon DE, Jang GM, Bouhaddou M, Xu J, Obernier K, White KM, O’Meara MJ, Rezelj VV, Guo JZ, Swaney DL. A SARS-CoV-2 protein interaction map reveals targets for drug repurposing. Nature. 2020;583:459–68.
Article CAS PubMed PubMed Central Google Scholar
Turanli B, Altay O, Borén J, Turkez H, Nielsen J, Uhlen M, Arga KY, Mardinoglu A. Systems biology based drug repositioning for development of cancer therapy. In Seminars in cancer biology. Elsevier; 2021. pp 47–58.
Poppe M, Wittig S, Jurida L, Bartkuhn M, Wilhelm J, Müller H, Beuerlein K, Karl N, Bhuju S, Ziebuhr J. The NF-κB-dependent and-independent transcriptome and chromatin landscapes of human coronavirus 229E-infected cells. PLoS Pathog. 2017;13: e1006286.
Article PubMed PubMed Central Google Scholar
Blanco-Melo D, Nilsson-Payant B, Liu W-C, Møller R, Panis M, Sachs D, Albrecht R. SARS-CoV-2 launches a unique transcriptional signature from in vitro, ex vivo, and in vivo systems. BioRxiv 2020. https://doi.org/10.1101/2020.03.24.004655
Alanis-Lobato G, Andrade-Navarro MA, Schaefer MH: HIPPIE v2. 0: enhancing meaningfulness and reliability of protein–protein interaction networks. Nucleic Acids Res 2016:gkw985.
Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, Simonovic M, Doncheva NT, Morris JH, Bork P. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47:D607–13.
Article CAS PubMed Google Scholar
Bozhilova LV, Whitmore AV, Wray J, Reinert G, Deane CM. Measuring rank robustness in scored protein interaction networks. BMC Bioinform. 2019;20:1–14.
Martin A, Ochagavia ME, Rabasa LC, Miranda J, Fernandez-de-Cossio J, Bringas R. BisoGenet: a new tool for gene network building, visualization and analysis. BMC Bioinform. 2010;11:1–9.
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13:2498–504.
Article CAS PubMed PubMed Central Google Scholar
Gould R. Graph theory. Courier Corporation; 2012.
Ser-Giacomi E, Baudena A, Rossi V, Follows M, Clayton S, Vasile R, López C, Hernández-García E. Lagrangian betweenness as a measure of bottlenecks in dynamical systems with oceanographic examples. Nat Commun. 2021;12:4935.
Article CAS PubMed PubMed Central Google Scholar
Yu H, Kim PM, Sprecher E, Trifonov V, Gerstein M. The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics. PLoS Comput Biol. 2007;3: e59.
Article PubMed PubMed Central Google Scholar
Mu Y, Wang J, Liu Z, Zhao Y, Zhang X, Jiao M, Lv J, Hao J, Kong Q. A method for tracing exogenous DNA uptake in live spermatozoa and embryos. Pol J Vet Sci. 2018.
Bader GD, Hogue CW. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinform. 2003;4:1–27.
Xiao F, Zuo Z, Cai G, Kang S, Gao X, Li T. miRecords: an integrated resource for microRNA–target interactions. Nucleic Acids Res. 2009;37:D105–10.
Article CAS PubMed Google Scholar
Huang H-Y, Lin Y-C-D, Li J, Huang K-Y, Shrestha S, Hong H-C, Tang Y, Chen Y-G, Jin C-N, Yu Y. miRTarBase 2020: updates to the experimentally validated microRNA–target interaction database. Nucleic Acids Res. 2020;48:D148-D154.
Wingender E, Dietze P, Karas H, Knüppel R. TRANSFAC: a database on transcription factors and their DNA binding sites. Nucleic Acids Res. 1996;24:238–41.
Article CAS PubMed PubMed Central Google Scholar
Han H, Cho J-W, Lee S, Yun A, Kim H, Bae D, Yang S, Kim CY, Lee M, Kim E. TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions. Nucleic Acids Res. 2018;46:D380–6.
Article CAS PubMed Google Scholar
Tong Z, Cui Q, Wang J, Zhou Y. TransmiR v2. 0: an updated transcription factor-microRNA regulation database. Nucleic Acids Res. 2019;47:D253-D258.
Wernicke S, Rasche F. FANMOD: a tool for fast network motif detection. Bioinformatics. 2006;22:1152–3.
Article CAS PubMed Google Scholar
Dennis G, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA. DAVID: database for annotation, visualization, and integrated discovery. Genome Biol. 2003;4:1–11.
Marriott HM, Gascoyne KA, Gowda R, Geary I, Nicklin MJ, Iannelli F, Pozzi G, Mitchell TJ, Whyte MK, Sabroe I, Dockrell DH. Interleukin-1β regulates CXCL8 release and influences disease outcome in response to Streptococcus pneumoniae, defining intercellular cooperation between pulmonary epithelial cells and macrophages. Infect Immun. 2012;80:1140–9.
Article CAS PubMed PubMed Central Google Scholar
Xiong Y, Liu Y, Cao L, Wang D, Guo M, Jiang A, Guo D, Hu W, Yang J, Tang Z, et al. Transcriptomic characteristics of bronchoalveolar lavage fluid and peripheral blood mononuclear cells in COVID-19 patients. Emerg Microbes Infect. 2020;9:761–70.
Article CAS PubMed PubMed Central Google Scholar
Xu ZS, Shu T, Kang L, Wu D, Zhou X, Liao BW, Sun XL, Zhou X, Wang YY. Temporal profiling of plasma cytokines, chemokines and growth factors from mild, severe and fatal COVID-19 patients. Signal Transduct Target Ther. 2020;5:100.
Comments (0)