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Nam, Dougu
Bioinformatics Lab.
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Bioinformatics services for analyzing massive genomic datasets

Author(s)
Ko, GunhwanKim, Pan-GyuCho, YoungbumJeong, SeongmunKim, Jae-YoonKim, Kyoung HyounLee, Ho-YeonHan, JiyeonYu, NamheeHam, SeokjinJang, InsoonKang, ByungheeShin, SungukKim, LianLee, Seung-WonNam, DouguKim, Jihyun F.Kim, NamshinKim, Seon-YoungLee, SanghyukRoh, Tae-YoungLee, Byungwook
Issued Date
2020-03
DOI
10.5808/GI.2020.18.1.e8
URI
https://scholarworks.unist.ac.kr/handle/201301/48357
Fulltext
https://genominfo.org/journal/view.php?number=599
Citation
Genomics and Informatics, v.18, no.1
Abstract
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 down-stream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/. © 2020, Korea Genome Organization.
Publisher
Korea Genome Organization
ISSN
1598-866X
Keyword (Author)
Analysis pipelineCloud computingGenomic dataWeb serverWorkflow system

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