The identification of lung cancer gene-drug module based on multiplex networks algorithm / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 1111-1117, 2021.
Article
Dans Chinois
| WPRIM
| ID: wpr-921852
ABSTRACT
Using modular identification methods in gene-drug multiplex networks to infer new gene-drug associations can identify new therapeutic target genes for known drugs. In this paper, based on the gene expression data and drug response data of lung cancer in the genomics of drug sensitivity in cancer (GDSC) database, a multiple network algorithm is proposed. First, a heterogeneous network of genes of lung cancer and drugs in different cell lines is constructed, and then a network module identification method based on graph entropy is used. In this heterogeneous network, network modules are identified, and five lung cancer gene-drug association modules are identified through iterative convergence. Compared with other methods, the algorithm has better results in terms of running time, accuracy and robustness, and the identified modules have obvious biological significance. The research results in this article have guiding significance for the medication and treatment of lung cancer, and can provide references for the treatment of other diseases with the same targeted genes.
Texte intégral:
Disponible
Indice:
WPRIM (Pacifique occidental)
Sujet Principal:
Algorithmes
/
Préparations pharmaceutiques
/
Analyse de profil d'expression de gènes
/
Gènes tumoraux
/
Poumon
/
Tumeurs du poumon
Type d'étude:
Etude diagnostique
/
Étude pronostique
Limites du sujet:
Humains
langue:
Chinois
Texte intégral:
Journal of Biomedical Engineering
Année:
2021
Type:
Article
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