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10.1155/2020/4256301 http://scihub22266oqcxt.onion/10.1155/2020/4256301 32685484!7345912!32685484     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32685484&cmd=llinks): Failed to open stream: HTTP request failed! 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Identification of COVID-19 Infection-Related Human Genes Based on a Random Walk Model in a Virus-Human Protein Interaction Network |pdf=|usr=}}{{32685484}} gab.com Text Identification of COVID-19 Infection-Related Human Genes Based on a Random Walk Model in a Virus-Human Protein Interaction Network JO: Biomed Res Int http://www.kidney.de/pget.php?&tw=1&pmid=32685484 #FOAvip Coronaviruses are specific crown-shaped viruses that were first identified in the 1960s, and three typical examples of the most recent coronavirus disease outbreaks include severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19. Particularly, COVID-19 is currently causing a worldwide pandemic, threatening the health of human beings globally. The identification of viral pathogenic mechanisms is important for further developing effective drugs and targeted clinical treatment methods. The delayed revelation of viral infectious mechanisms is currently one of the technical obstacles in the prevention and treatment of infectious diseases. In this study, we proposed a random walk model to identify the potential pathological mechanisms of COVID-19 on a virus-human protein interaction network, and we effectively identified a group of proteins that have already been determined to be potentially important for COVID-19 infection and for similar SARS infections, which help further developing drugs and targeted therapeutic methods against COVID-19. Moreover, we constructed a standard computational workflow for predicting the pathological biomarkers and related pharmacological targets of infectious diseases. Twit Text FOAVip Identification of COVID-19 Infection-Related Human Genes Based on a Random Walk Model in a Virus-Human Protein Interaction Network ????Biomed Res Int http://www.kidney.de/pget.php?&tw=1&pmid=32685484 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32685484 #FOAvip English Wikipedia <ref>{{Cite pmid|32685484}}</ref> Identification of COVID-19 Infection-Related Human Genes Based on a Random Walk Model in a Virus-Human Protein Interaction Network #MMPMID32685484 Zhang Y; Zeng T; Chen L; Ding S; Huang T; Cai YD Biomed Res Int 2020[]; 2020 (ä): 4256301 PMID32685484show ga Coronaviruses are specific crown-shaped viruses that were first identified in the 1960s, and three typical examples of the most recent coronavirus disease outbreaks include severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19. Particularly, COVID-19 is currently causing a worldwide pandemic, threatening the health of human beings globally. The identification of viral pathogenic mechanisms is important for further developing effective drugs and targeted clinical treatment methods. The delayed revelation of viral infectious mechanisms is currently one of the technical obstacles in the prevention and treatment of infectious diseases. In this study, we proposed a random walk model to identify the potential pathological mechanisms of COVID-19 on a virus-human protein interaction network, and we effectively identified a group of proteins that have already been determined to be potentially important for COVID-19 infection and for similar SARS infections, which help further developing drugs and targeted therapeutic methods against COVID-19. Moreover, we constructed a standard computational workflow for predicting the pathological biomarkers and related pharmacological targets of infectious diseases. |Betacoronavirus/isolation & purification[MESH] |Biomarkers/analysis[MESH] |COVID-19[MESH] |Coronavirus Infections/diagnosis/*genetics/virology[MESH] |Humans[MESH] |Models, Genetic[MESH] |Pandemics[MESH] |Pneumonia, Viral/diagnosis/*genetics/virology[MESH] |Protein Interaction Maps[MESH] |SARS-CoV-2[MESH]Identification of COVID-19 Infection-Related Human Genes Based on a Ra(epmc).pdf DeepDyve Pubget Overpricing