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Translational Bioinformatics for Cholangiocarcinoma: Opportunities and Challenges

Translational bioinformatics is becoming a driven force and a new scientific paradigm for cancer research in the era of big data. To promote the cross-disciplinary communication and research, we take cholangiocarcinoma as an example to review the present status and the future perspectives of the bio...

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Detalles Bibliográficos
Autores principales: Qian, Fuliang, Guo, Junping, Jiang, Zhi, Shen, Bairong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6036745/
https://www.ncbi.nlm.nih.gov/pubmed/29989102
http://dx.doi.org/10.7150/ijbs.24622
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author Qian, Fuliang
Guo, Junping
Jiang, Zhi
Shen, Bairong
author_facet Qian, Fuliang
Guo, Junping
Jiang, Zhi
Shen, Bairong
author_sort Qian, Fuliang
collection PubMed
description Translational bioinformatics is becoming a driven force and a new scientific paradigm for cancer research in the era of big data. To promote the cross-disciplinary communication and research, we take cholangiocarcinoma as an example to review the present status and the future perspectives of the bioinformatics models applied in cancer study. We first summarize the present application of computational methods to the study of cholangiocarcinoma ranged from pattern recognition of biological data, knowledge based data annotation to systems biological level modeling and clinical translation. Then the future opportunities and challenges about database or knowledge base building, novel model developing and molecular mechanism exploring as well as the intelligent decision supporting system construction for the precision diagnosis, prognosis and treatment of cholangiocarcinoma are discussed.
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spelling pubmed-60367452018-07-09 Translational Bioinformatics for Cholangiocarcinoma: Opportunities and Challenges Qian, Fuliang Guo, Junping Jiang, Zhi Shen, Bairong Int J Biol Sci Review Translational bioinformatics is becoming a driven force and a new scientific paradigm for cancer research in the era of big data. To promote the cross-disciplinary communication and research, we take cholangiocarcinoma as an example to review the present status and the future perspectives of the bioinformatics models applied in cancer study. We first summarize the present application of computational methods to the study of cholangiocarcinoma ranged from pattern recognition of biological data, knowledge based data annotation to systems biological level modeling and clinical translation. Then the future opportunities and challenges about database or knowledge base building, novel model developing and molecular mechanism exploring as well as the intelligent decision supporting system construction for the precision diagnosis, prognosis and treatment of cholangiocarcinoma are discussed. Ivyspring International Publisher 2018-05-22 /pmc/articles/PMC6036745/ /pubmed/29989102 http://dx.doi.org/10.7150/ijbs.24622 Text en © Ivyspring International Publisher This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Review
Qian, Fuliang
Guo, Junping
Jiang, Zhi
Shen, Bairong
Translational Bioinformatics for Cholangiocarcinoma: Opportunities and Challenges
title Translational Bioinformatics for Cholangiocarcinoma: Opportunities and Challenges
title_full Translational Bioinformatics for Cholangiocarcinoma: Opportunities and Challenges
title_fullStr Translational Bioinformatics for Cholangiocarcinoma: Opportunities and Challenges
title_full_unstemmed Translational Bioinformatics for Cholangiocarcinoma: Opportunities and Challenges
title_short Translational Bioinformatics for Cholangiocarcinoma: Opportunities and Challenges
title_sort translational bioinformatics for cholangiocarcinoma: opportunities and challenges
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6036745/
https://www.ncbi.nlm.nih.gov/pubmed/29989102
http://dx.doi.org/10.7150/ijbs.24622
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