Identification of colorectal cancer related genes with mRMR and shortest path in protein-protein interaction network.

One of the most important and challenging problems in biomedicine and genomics is how to identify the disease genes. In this study, we developed a computational method to identify colorectal cancer-related genes based on (i) the gene expression profiles, and (ii) the shortest path analysis of functi...

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Autores principales: Bi-Qing Li, Tao Huang, Lei Liu, Yu-Dong Cai, Kuo-Chen Chou
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Publicado: Public Library of Science (PLoS) 2012
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Acceso en línea:https://doaj.org/article/44c04ca4ede04cd1bf7af0cbe9cc3e1b
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spelling oai:doaj.org-article:44c04ca4ede04cd1bf7af0cbe9cc3e1b2021-11-18T07:23:18ZIdentification of colorectal cancer related genes with mRMR and shortest path in protein-protein interaction network.1932-620310.1371/journal.pone.0033393https://doaj.org/article/44c04ca4ede04cd1bf7af0cbe9cc3e1b2012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22496748/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203One of the most important and challenging problems in biomedicine and genomics is how to identify the disease genes. In this study, we developed a computational method to identify colorectal cancer-related genes based on (i) the gene expression profiles, and (ii) the shortest path analysis of functional protein association networks. The former has been used to select differentially expressed genes as disease genes for quite a long time, while the latter has been widely used to study the mechanism of diseases. With the existing protein-protein interaction data from STRING (Search Tool for the Retrieval of Interacting Genes), a weighted functional protein association network was constructed. By means of the mRMR (Maximum Relevance Minimum Redundancy) approach, six genes were identified that can distinguish the colorectal tumors and normal adjacent colonic tissues from their gene expression profiles. Meanwhile, according to the shortest path approach, we further found an additional 35 genes, of which some have been reported to be relevant to colorectal cancer and some are very likely to be relevant to it. Interestingly, the genes we identified from both the gene expression profiles and the functional protein association network have more cancer genes than the genes identified from the gene expression profiles alone. Besides, these genes also had greater functional similarity with the reported colorectal cancer genes than the genes identified from the gene expression profiles alone. All these indicate that our method as presented in this paper is quite promising. The method may become a useful tool, or at least plays a complementary role to the existing method, for identifying colorectal cancer genes. It has not escaped our notice that the method can be applied to identify the genes of other diseases as well.Bi-Qing LiTao HuangLei LiuYu-Dong CaiKuo-Chen ChouPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 4, p e33393 (2012)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Bi-Qing Li
Tao Huang
Lei Liu
Yu-Dong Cai
Kuo-Chen Chou
Identification of colorectal cancer related genes with mRMR and shortest path in protein-protein interaction network.
description One of the most important and challenging problems in biomedicine and genomics is how to identify the disease genes. In this study, we developed a computational method to identify colorectal cancer-related genes based on (i) the gene expression profiles, and (ii) the shortest path analysis of functional protein association networks. The former has been used to select differentially expressed genes as disease genes for quite a long time, while the latter has been widely used to study the mechanism of diseases. With the existing protein-protein interaction data from STRING (Search Tool for the Retrieval of Interacting Genes), a weighted functional protein association network was constructed. By means of the mRMR (Maximum Relevance Minimum Redundancy) approach, six genes were identified that can distinguish the colorectal tumors and normal adjacent colonic tissues from their gene expression profiles. Meanwhile, according to the shortest path approach, we further found an additional 35 genes, of which some have been reported to be relevant to colorectal cancer and some are very likely to be relevant to it. Interestingly, the genes we identified from both the gene expression profiles and the functional protein association network have more cancer genes than the genes identified from the gene expression profiles alone. Besides, these genes also had greater functional similarity with the reported colorectal cancer genes than the genes identified from the gene expression profiles alone. All these indicate that our method as presented in this paper is quite promising. The method may become a useful tool, or at least plays a complementary role to the existing method, for identifying colorectal cancer genes. It has not escaped our notice that the method can be applied to identify the genes of other diseases as well.
format article
author Bi-Qing Li
Tao Huang
Lei Liu
Yu-Dong Cai
Kuo-Chen Chou
author_facet Bi-Qing Li
Tao Huang
Lei Liu
Yu-Dong Cai
Kuo-Chen Chou
author_sort Bi-Qing Li
title Identification of colorectal cancer related genes with mRMR and shortest path in protein-protein interaction network.
title_short Identification of colorectal cancer related genes with mRMR and shortest path in protein-protein interaction network.
title_full Identification of colorectal cancer related genes with mRMR and shortest path in protein-protein interaction network.
title_fullStr Identification of colorectal cancer related genes with mRMR and shortest path in protein-protein interaction network.
title_full_unstemmed Identification of colorectal cancer related genes with mRMR and shortest path in protein-protein interaction network.
title_sort identification of colorectal cancer related genes with mrmr and shortest path in protein-protein interaction network.
publisher Public Library of Science (PLoS)
publishDate 2012
url https://doaj.org/article/44c04ca4ede04cd1bf7af0cbe9cc3e1b
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AT taohuang identificationofcolorectalcancerrelatedgeneswithmrmrandshortestpathinproteinproteininteractionnetwork
AT leiliu identificationofcolorectalcancerrelatedgeneswithmrmrandshortestpathinproteinproteininteractionnetwork
AT yudongcai identificationofcolorectalcancerrelatedgeneswithmrmrandshortestpathinproteinproteininteractionnetwork
AT kuochenchou identificationofcolorectalcancerrelatedgeneswithmrmrandshortestpathinproteinproteininteractionnetwork
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