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Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms
Advances of high-throughput technologies have rapidly produced more and more data from DNAs and RNAs to proteins, especially large volumes of genome-scale data. However, connection of the genomic information to cellular functions and biological behaviours relies on the development of effective appro...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4304187/ https://www.ncbi.nlm.nih.gov/pubmed/25559210 http://dx.doi.org/10.1186/1471-2105-15-S17-I1 |
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author | Yang, Jack Y Dunker, A Keith Liu, Jun S Qin, Xiang Arabnia, Hamid R Yang, William Niemierko, Andrzej Chen, Zhongxue Luo, Zuojie Wang, Liangjiang Liu, Yunlong Xu, Dong Deng, Youping Tong, Weida Yang, Mary Qu |
author_facet | Yang, Jack Y Dunker, A Keith Liu, Jun S Qin, Xiang Arabnia, Hamid R Yang, William Niemierko, Andrzej Chen, Zhongxue Luo, Zuojie Wang, Liangjiang Liu, Yunlong Xu, Dong Deng, Youping Tong, Weida Yang, Mary Qu |
author_sort | Yang, Jack Y |
collection | PubMed |
description | Advances of high-throughput technologies have rapidly produced more and more data from DNAs and RNAs to proteins, especially large volumes of genome-scale data. However, connection of the genomic information to cellular functions and biological behaviours relies on the development of effective approaches at higher systems level. In particular, advances in RNA-Seq technology has helped the studies of transcriptome, RNA expressed from the genome, while systems biology on the other hand provides more comprehensive pictures, from which genes and proteins actively interact to lead to cellular behaviours and physiological phenotypes. As biological interactions mediate many biological processes that are essential for cellular function or disease development, it is important to systematically identify genomic information including genetic mutations from GWAS (genome-wide association study), differentially expressed genes, bidirectional promoters, intrinsic disordered proteins (IDP) and protein interactions to gain deep insights into the underlying mechanisms of gene regulations and networks. Furthermore, bidirectional promoters can co-regulate many biological pathways, where the roles of bidirectional promoters can be studied systematically for identifying co-regulating genes at interactive network level. Combining information from different but related studies can ultimately help revealing the landscape of molecular mechanisms underlying complex diseases such as cancer. |
format | Online Article Text |
id | pubmed-4304187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43041872015-02-09 Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms Yang, Jack Y Dunker, A Keith Liu, Jun S Qin, Xiang Arabnia, Hamid R Yang, William Niemierko, Andrzej Chen, Zhongxue Luo, Zuojie Wang, Liangjiang Liu, Yunlong Xu, Dong Deng, Youping Tong, Weida Yang, Mary Qu BMC Bioinformatics Introduction Advances of high-throughput technologies have rapidly produced more and more data from DNAs and RNAs to proteins, especially large volumes of genome-scale data. However, connection of the genomic information to cellular functions and biological behaviours relies on the development of effective approaches at higher systems level. In particular, advances in RNA-Seq technology has helped the studies of transcriptome, RNA expressed from the genome, while systems biology on the other hand provides more comprehensive pictures, from which genes and proteins actively interact to lead to cellular behaviours and physiological phenotypes. As biological interactions mediate many biological processes that are essential for cellular function or disease development, it is important to systematically identify genomic information including genetic mutations from GWAS (genome-wide association study), differentially expressed genes, bidirectional promoters, intrinsic disordered proteins (IDP) and protein interactions to gain deep insights into the underlying mechanisms of gene regulations and networks. Furthermore, bidirectional promoters can co-regulate many biological pathways, where the roles of bidirectional promoters can be studied systematically for identifying co-regulating genes at interactive network level. Combining information from different but related studies can ultimately help revealing the landscape of molecular mechanisms underlying complex diseases such as cancer. BioMed Central 2014-12-16 /pmc/articles/PMC4304187/ /pubmed/25559210 http://dx.doi.org/10.1186/1471-2105-15-S17-I1 Text en Copyright © 2014 Yang et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Introduction Yang, Jack Y Dunker, A Keith Liu, Jun S Qin, Xiang Arabnia, Hamid R Yang, William Niemierko, Andrzej Chen, Zhongxue Luo, Zuojie Wang, Liangjiang Liu, Yunlong Xu, Dong Deng, Youping Tong, Weida Yang, Mary Qu Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms |
title | Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms |
title_full | Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms |
title_fullStr | Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms |
title_full_unstemmed | Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms |
title_short | Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms |
title_sort | advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms |
topic | Introduction |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4304187/ https://www.ncbi.nlm.nih.gov/pubmed/25559210 http://dx.doi.org/10.1186/1471-2105-15-S17-I1 |
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