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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korea Genome Organization
2020
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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/. |
format | Online Article Text |
id | pubmed-7120352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Korea Genome Organization |
record_format | MEDLINE/PubMed |
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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