Bioinformatics services for analyzing massive genomic datasets

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Bioinformatics services for analyzing massive genomic datasets
Gunhwan KoPan-Gyu Kim; Youngbum Cho; Seongmun Jeong; Jae-Yoon Kim; Kyoung Hyoun Kim; Ho-Yeon Lee; J Han; N Yu; S Ham; I Jang; B Kang; S Shin; L Kim; S W Lee; D Nam; J F Kim; Namshin Kim; Seon-Young Kim; S Lee; T Y Roh; Byunguk Lee
Bibliographic Citation
Genomics & Informatics, vol. 18, no. 1, pp. e8-e8
Publication Year
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
analysis pipelinecloud computinggenomic dataweb serverworkflow system
Korea Soc-Assoc-Inst
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Division of Biomedical Research > Personalized Genomic Medicine Research Center > 1. Journal Articles
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