| Genes | |
| Computational Analysis of the Global Effects of Ly6E in the Immune Response to Coronavirus Infection Using Gene Networks | |
| Federico Divina1  DomingoS. Rodriguez-Baena1  Francisco Gómez-Vela1  Miguel García-Torres1  FernandoM. Delgado-Chaves1  | |
| [1] Pablo de Olavide University, Carretera de Utrera km 1, ES-41013 Seville, Spain; | |
| 关键词: gene co-expression network; murine coronavirus; viral infection; immune response; data mining; systems biology; | |
| DOI : 10.3390/genes11070831 | |
| 来源: DOAJ | |
【 摘 要 】
Gene networks have arisen as a promising tool in the comprehensive modeling and analysis of complex diseases. Particularly in viral infections, the understanding of the host-pathogen mechanisms, and the immune response to these, is considered a major goal for the rational design of appropriate therapies. For this reason, the use of gene networks may well encourage therapy-associated research in the context of the coronavirus pandemic, orchestrating experimental scrutiny and reducing costs. In this work, gene co-expression networks were reconstructed from RNA-Seq expression data with the aim of analyzing the time-resolved effects of gene Ly6E in the immune response against the coronavirus responsible for murine hepatitis (MHV). Through the integration of differential expression analyses and reconstructed networks exploration, significant differences in the immune response to virus were observed in Ly6E
【 授权许可】
Unknown