Prioritizing Susceptible Genes for Thyroid Cancer Based on Gene Interaction Network.
Adaboost
deep neural network
gene interaction
genetic testing
thyroid cancer
Journal
Frontiers in cell and developmental biology
ISSN: 2296-634X
Titre abrégé: Front Cell Dev Biol
Pays: Switzerland
ID NLM: 101630250
Informations de publication
Date de publication:
2021
2021
Historique:
received:
12
07
2021
accepted:
02
08
2021
entrez:
9
9
2021
pubmed:
10
9
2021
medline:
10
9
2021
Statut:
epublish
Résumé
Thyroid cancer ranks second in the incidence rate of endocrine malignant cancer. Thyroid cancer is usually asymptomatic at the initial stage, which makes patients easily miss the early treatment time. Combining genetic testing with imaging can greatly improve the diagnostic efficiency of thyroid cancer. Researchers have discovered many genes related to thyroid cancer. However, the effects of these genes on thyroid cancer are different. We hypothesize that there is a stronger interaction between the core genes that cause thyroid cancer. Based on this hypothesis, we constructed an interaction network of thyroid cancer-related genes. We traversed the network through random walks, and sorted thyroid cancer-related genes through ADNN which is fusion of Adaboost and deep neural network (DNN). In addition, we discovered more thyroid cancer-related genes by ADNN. In order to verify the accuracy of ADNN, we conducted a fivefold cross-validation. ADNN achieved AUC of 0.85 and AUPR of 0.81, which are more accurate than other methods.
Identifiants
pubmed: 34497810
doi: 10.3389/fcell.2021.740267
pmc: PMC8421023
doi:
Types de publication
Journal Article
Langues
eng
Pagination
740267Informations de copyright
Copyright © 2021 Zhong, Xie, Jiang, Deng, Gan, Feng, Cai, Liu, Shen, Miao and Xu.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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