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Identification of Novel Thyroid Cancer-Related Genes and Chemicals Using Shortest Path Algorithm

Thyroid cancer is a typical endocrine malignancy. In the past three decades, the continued growth of its incidence has made it urgent to design effective treatments to treat this disease. To this end, it is necessary to uncover the mechanism underlying this disease. Identification of thyroid cancer-...

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Detalles Bibliográficos
Autores principales: Jiang, Yang, Zhang, Peiwei, Li, Li-Peng, He, Yi-Chun, Gao, Ru-jian, Gao, Yu-Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4385622/
https://www.ncbi.nlm.nih.gov/pubmed/25874234
http://dx.doi.org/10.1155/2015/964795
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author Jiang, Yang
Zhang, Peiwei
Li, Li-Peng
He, Yi-Chun
Gao, Ru-jian
Gao, Yu-Fei
author_facet Jiang, Yang
Zhang, Peiwei
Li, Li-Peng
He, Yi-Chun
Gao, Ru-jian
Gao, Yu-Fei
author_sort Jiang, Yang
collection PubMed
description Thyroid cancer is a typical endocrine malignancy. In the past three decades, the continued growth of its incidence has made it urgent to design effective treatments to treat this disease. To this end, it is necessary to uncover the mechanism underlying this disease. Identification of thyroid cancer-related genes and chemicals is helpful to understand the mechanism of thyroid cancer. In this study, we generalized some previous methods to discover both disease genes and chemicals. The method was based on shortest path algorithm and applied to discover novel thyroid cancer-related genes and chemicals. The analysis of the final obtained genes and chemicals suggests that some of them are crucial to the formation and development of thyroid cancer. It is indicated that the proposed method is effective for the discovery of novel disease genes and chemicals.
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spelling pubmed-43856222015-04-13 Identification of Novel Thyroid Cancer-Related Genes and Chemicals Using Shortest Path Algorithm Jiang, Yang Zhang, Peiwei Li, Li-Peng He, Yi-Chun Gao, Ru-jian Gao, Yu-Fei Biomed Res Int Research Article Thyroid cancer is a typical endocrine malignancy. In the past three decades, the continued growth of its incidence has made it urgent to design effective treatments to treat this disease. To this end, it is necessary to uncover the mechanism underlying this disease. Identification of thyroid cancer-related genes and chemicals is helpful to understand the mechanism of thyroid cancer. In this study, we generalized some previous methods to discover both disease genes and chemicals. The method was based on shortest path algorithm and applied to discover novel thyroid cancer-related genes and chemicals. The analysis of the final obtained genes and chemicals suggests that some of them are crucial to the formation and development of thyroid cancer. It is indicated that the proposed method is effective for the discovery of novel disease genes and chemicals. Hindawi Publishing Corporation 2015 2015-03-22 /pmc/articles/PMC4385622/ /pubmed/25874234 http://dx.doi.org/10.1155/2015/964795 Text en Copyright © 2015 Yang Jiang et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Jiang, Yang
Zhang, Peiwei
Li, Li-Peng
He, Yi-Chun
Gao, Ru-jian
Gao, Yu-Fei
Identification of Novel Thyroid Cancer-Related Genes and Chemicals Using Shortest Path Algorithm
title Identification of Novel Thyroid Cancer-Related Genes and Chemicals Using Shortest Path Algorithm
title_full Identification of Novel Thyroid Cancer-Related Genes and Chemicals Using Shortest Path Algorithm
title_fullStr Identification of Novel Thyroid Cancer-Related Genes and Chemicals Using Shortest Path Algorithm
title_full_unstemmed Identification of Novel Thyroid Cancer-Related Genes and Chemicals Using Shortest Path Algorithm
title_short Identification of Novel Thyroid Cancer-Related Genes and Chemicals Using Shortest Path Algorithm
title_sort identification of novel thyroid cancer-related genes and chemicals using shortest path algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4385622/
https://www.ncbi.nlm.nih.gov/pubmed/25874234
http://dx.doi.org/10.1155/2015/964795
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