select ad.sno,ad.journal,ad.title,ad.author_names,ad.abstract,ad.abstractlink,j.j_name,vi.* from articles_data ad left join journals j on j.journal=ad.journal left join vol_issues vi on vi.issue_id_en=ad.issue_id where ad.sno_en='57796' and ad.lang_id='3' and j.lang_id='3' and vi.lang_id='3'
ISSN: 2157-7609
Gustavo Simões Carnivali1*, Diego Simões Carnivali2
The viral disease COVID-19 first emerged in China in December 2019 and has already spread worldwide. Due to its high transmission rate and considerable number of deaths, this disease has since become a major topic of scientific studies, such as those that suggest the use of existing drugs to treat COVID-19. The aim of this study is to analyze and characterize the genetic interactions of drugs indicated by other studies for the treatment of this disease. Based on a gene co-expression network (GCN), we propose parameters that assess the connection between the drugs studied. These parameters allow researchers to identify drugs with similar functionality and to better understand the performance of these drugs when combined. Finally, this study presents two tables with the calculated measurements between all drugs, as well as previous analyses on the results found. This study contributes to increase the assertiveness in the prescription of more than one medicine for the treatment of COVID-19.