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Biological Networks for Cancer Candidate Biomarkers Discovery

Due to its extraordinary heterogeneity and complexity, cancer is often proposed as a model case of a systems biology disease or network disease. There is a critical need of effective biomarkers for cancer diagnosis and/or outcome prediction from system level analyses. Methods based on integrating om...

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Detalles Bibliográficos
Autores principales: Yan, Wenying, Xue, Wenjin, Chen, Jiajia, Hu, Guang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Libertas Academica 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5012434/
https://www.ncbi.nlm.nih.gov/pubmed/27625573
http://dx.doi.org/10.4137/CIN.S39458
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author Yan, Wenying
Xue, Wenjin
Chen, Jiajia
Hu, Guang
author_facet Yan, Wenying
Xue, Wenjin
Chen, Jiajia
Hu, Guang
author_sort Yan, Wenying
collection PubMed
description Due to its extraordinary heterogeneity and complexity, cancer is often proposed as a model case of a systems biology disease or network disease. There is a critical need of effective biomarkers for cancer diagnosis and/or outcome prediction from system level analyses. Methods based on integrating omics data into networks have the potential to revolutionize the identification of cancer biomarkers. Deciphering the biological networks underlying cancer is undoubtedly important for understanding the molecular mechanisms of the disease and identifying effective biomarkers. In this review, the networks constructed for cancer biomarker discovery based on different omics level data are described and illustrated from recent advances in the field.
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spelling pubmed-50124342016-09-13 Biological Networks for Cancer Candidate Biomarkers Discovery Yan, Wenying Xue, Wenjin Chen, Jiajia Hu, Guang Cancer Inform Review Due to its extraordinary heterogeneity and complexity, cancer is often proposed as a model case of a systems biology disease or network disease. There is a critical need of effective biomarkers for cancer diagnosis and/or outcome prediction from system level analyses. Methods based on integrating omics data into networks have the potential to revolutionize the identification of cancer biomarkers. Deciphering the biological networks underlying cancer is undoubtedly important for understanding the molecular mechanisms of the disease and identifying effective biomarkers. In this review, the networks constructed for cancer biomarker discovery based on different omics level data are described and illustrated from recent advances in the field. Libertas Academica 2016-09-04 /pmc/articles/PMC5012434/ /pubmed/27625573 http://dx.doi.org/10.4137/CIN.S39458 Text en © 2016 the author(s), publisher and licensee Libertas Academica Ltd. This is an open-access article distributed under the terms of the Creative Commons CC-BY-NC 3.0 license.
spellingShingle Review
Yan, Wenying
Xue, Wenjin
Chen, Jiajia
Hu, Guang
Biological Networks for Cancer Candidate Biomarkers Discovery
title Biological Networks for Cancer Candidate Biomarkers Discovery
title_full Biological Networks for Cancer Candidate Biomarkers Discovery
title_fullStr Biological Networks for Cancer Candidate Biomarkers Discovery
title_full_unstemmed Biological Networks for Cancer Candidate Biomarkers Discovery
title_short Biological Networks for Cancer Candidate Biomarkers Discovery
title_sort biological networks for cancer candidate biomarkers discovery
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5012434/
https://www.ncbi.nlm.nih.gov/pubmed/27625573
http://dx.doi.org/10.4137/CIN.S39458
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