针对COVID-19的药物基因相互作用分析

G. Carnivali, Diego Simes Carnivali
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引用次数: 0

摘要

2019年12月,新型冠状病毒病首次在中国出现,目前已在全球蔓延。由于其高传播率和相当多的死亡人数,这种疾病已成为科学研究的一个主要主题,例如建议使用现有药物治疗COVID-19。本研究的目的是分析和表征其他研究表明用于治疗这种疾病的药物的遗传相互作用。基于基因共表达网络(GCN),我们提出了评估所研究药物之间联系的参数。这些参数使研究人员能够识别具有类似功能的药物,并更好地了解这些药物联合使用时的性能。最后,本研究提供了两个表格,其中包含了所有药物之间的计算测量值,以及之前对结果的分析。这项研究有助于增加对COVID-19治疗的多种药物处方的自信。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ANALYSIS OF GENETIC INTERACTIONS OF MEDICINES INDICATED FOR COVID-19
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.
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