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Bioinformatics services for analyzing massive genomic datasets

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational...

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Autores principales: Ko, Gunhwan, Kim, Pan-Gyu, Cho, Youngbum, Jeong, Seongmun, Kim, Jae-Yoon, Kim, Kyoung Hyoun, Lee, Ho-Yeon, Han, Jiyeon, Yu, Namhee, Ham, Seokjin, Jang, Insoon, Kang, Byunghee, Shin, Sunguk, Kim, Lian, Lee, Seung-Won, Nam, Dougu, Kim, Jihyun F., Kim, Namshin, Kim, Seon-Young, Lee, Sanghyuk, Roh, Tae-Young, Lee, Byungwook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Genome Organization 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120352/
https://www.ncbi.nlm.nih.gov/pubmed/32224841
http://dx.doi.org/10.5808/GI.2020.18.1.e8
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author Ko, Gunhwan
Kim, Pan-Gyu
Cho, Youngbum
Jeong, Seongmun
Kim, Jae-Yoon
Kim, Kyoung Hyoun
Lee, Ho-Yeon
Han, Jiyeon
Yu, Namhee
Ham, Seokjin
Jang, Insoon
Kang, Byunghee
Shin, Sunguk
Kim, Lian
Lee, Seung-Won
Nam, Dougu
Kim, Jihyun F.
Kim, Namshin
Kim, Seon-Young
Lee, Sanghyuk
Roh, Tae-Young
Lee, Byungwook
author_facet Ko, Gunhwan
Kim, Pan-Gyu
Cho, Youngbum
Jeong, Seongmun
Kim, Jae-Yoon
Kim, Kyoung Hyoun
Lee, Ho-Yeon
Han, Jiyeon
Yu, Namhee
Ham, Seokjin
Jang, Insoon
Kang, Byunghee
Shin, Sunguk
Kim, Lian
Lee, Seung-Won
Nam, Dougu
Kim, Jihyun F.
Kim, Namshin
Kim, Seon-Young
Lee, Sanghyuk
Roh, Tae-Young
Lee, Byungwook
author_sort Ko, Gunhwan
collection PubMed
description The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.
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spelling pubmed-71203522020-04-09 Bioinformatics services for analyzing massive genomic datasets Ko, Gunhwan Kim, Pan-Gyu Cho, Youngbum Jeong, Seongmun Kim, Jae-Yoon Kim, Kyoung Hyoun Lee, Ho-Yeon Han, Jiyeon Yu, Namhee Ham, Seokjin Jang, Insoon Kang, Byunghee Shin, Sunguk Kim, Lian Lee, Seung-Won Nam, Dougu Kim, Jihyun F. Kim, Namshin Kim, Seon-Young Lee, Sanghyuk Roh, Tae-Young Lee, Byungwook Genomics Inform Original Article The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/. Korea Genome Organization 2020-03-31 /pmc/articles/PMC7120352/ /pubmed/32224841 http://dx.doi.org/10.5808/GI.2020.18.1.e8 Text en (c) 2020, Korea Genome Organization (CC) This is an open-access article distributed under the terms of the Creative Commons Attribution license(https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Ko, Gunhwan
Kim, Pan-Gyu
Cho, Youngbum
Jeong, Seongmun
Kim, Jae-Yoon
Kim, Kyoung Hyoun
Lee, Ho-Yeon
Han, Jiyeon
Yu, Namhee
Ham, Seokjin
Jang, Insoon
Kang, Byunghee
Shin, Sunguk
Kim, Lian
Lee, Seung-Won
Nam, Dougu
Kim, Jihyun F.
Kim, Namshin
Kim, Seon-Young
Lee, Sanghyuk
Roh, Tae-Young
Lee, Byungwook
Bioinformatics services for analyzing massive genomic datasets
title Bioinformatics services for analyzing massive genomic datasets
title_full Bioinformatics services for analyzing massive genomic datasets
title_fullStr Bioinformatics services for analyzing massive genomic datasets
title_full_unstemmed Bioinformatics services for analyzing massive genomic datasets
title_short Bioinformatics services for analyzing massive genomic datasets
title_sort bioinformatics services for analyzing massive genomic datasets
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120352/
https://www.ncbi.nlm.nih.gov/pubmed/32224841
http://dx.doi.org/10.5808/GI.2020.18.1.e8
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