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Prioritizing Susceptible Genes for Thyroid Cancer Based on Gene Interaction Network
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 can...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8421023/ https://www.ncbi.nlm.nih.gov/pubmed/34497810 http://dx.doi.org/10.3389/fcell.2021.740267 |
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author | Zhong, Lin-kun Xie, Chang-lian Jiang, Shan Deng, Xing-yan Gan, Xiao-xiong Feng, Jian-hua Cai, Wen-song Liu, Chi-zhuai Shen, Fei Miao, Jian-hang Xu, Bo |
author_facet | Zhong, Lin-kun Xie, Chang-lian Jiang, Shan Deng, Xing-yan Gan, Xiao-xiong Feng, Jian-hua Cai, Wen-song Liu, Chi-zhuai Shen, Fei Miao, Jian-hang Xu, Bo |
author_sort | Zhong, Lin-kun |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8421023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84210232021-09-07 Prioritizing Susceptible Genes for Thyroid Cancer Based on Gene Interaction Network Zhong, Lin-kun Xie, Chang-lian Jiang, Shan Deng, Xing-yan Gan, Xiao-xiong Feng, Jian-hua Cai, Wen-song Liu, Chi-zhuai Shen, Fei Miao, Jian-hang Xu, Bo Front Cell Dev Biol Cell and Developmental Biology 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. Frontiers Media S.A. 2021-08-23 /pmc/articles/PMC8421023/ /pubmed/34497810 http://dx.doi.org/10.3389/fcell.2021.740267 Text en Copyright © 2021 Zhong, Xie, Jiang, Deng, Gan, Feng, Cai, Liu, Shen, Miao and Xu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cell and Developmental Biology Zhong, Lin-kun Xie, Chang-lian Jiang, Shan Deng, Xing-yan Gan, Xiao-xiong Feng, Jian-hua Cai, Wen-song Liu, Chi-zhuai Shen, Fei Miao, Jian-hang Xu, Bo Prioritizing Susceptible Genes for Thyroid Cancer Based on Gene Interaction Network |
title | Prioritizing Susceptible Genes for Thyroid Cancer Based on Gene Interaction Network |
title_full | Prioritizing Susceptible Genes for Thyroid Cancer Based on Gene Interaction Network |
title_fullStr | Prioritizing Susceptible Genes for Thyroid Cancer Based on Gene Interaction Network |
title_full_unstemmed | Prioritizing Susceptible Genes for Thyroid Cancer Based on Gene Interaction Network |
title_short | Prioritizing Susceptible Genes for Thyroid Cancer Based on Gene Interaction Network |
title_sort | prioritizing susceptible genes for thyroid cancer based on gene interaction network |
topic | Cell and Developmental Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8421023/ https://www.ncbi.nlm.nih.gov/pubmed/34497810 http://dx.doi.org/10.3389/fcell.2021.740267 |
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