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The only cloud-based integrated data analysis service in Korea

High-speed analysis of genomic big data using the big data platform built with KOBIC's technology

Bio-Express

"Integrated analytics platform for better genomic big data analysis"

Bio-Express is an intuitive and open integrated analytics system for analyzing genomic big data based on one enterprise-class server platform.

Why Bio-Express?

The policy to share and disclose is supported in order to understand the analysis technology required to analyze genomes, and to enable the reuse of workflows and programs. Hence, everyone can readily access and utilize the components and resources of Bio-Express for collaboration and the reproduction of analysis contents.

Bio-Express integrated analytics platform

Bio-Express 통합 분석 플랫폼

Bio-Express high-performance infrastructure system

Bio-Express 고성능 인프라 시스템

Bio-Express genomic big data analysis environment

Users can readily use all program tools and services provided by Bio-Express to analyze and generate genomic big data. Users can upload and access a large volume of data quickly and readily. Users can also run high-speed analysis by utilizing individuals' data and various open data analysis sources in an intuitive and visual workflow environment.

Latest analysis environment

Provides a research analysis environment where users can use the latest analysis tools by employing current research trends

Processes large volumes of data

Provides efficient analysis services capable of analyzing and processing genomic big data accurately and at high speed

Convenient analysis tools

Users can learn and analyze easily using analysis services based on a convenient interface and open pipelines

High-performance infrastructure system

Provides a computing infrastructure capable of performing cloud-based analysis of a large volume of data at high speed

Shared analytics platform

Reliable information sharing with the support of community service among expert researchers in various fields

Elaborate analysis, intuitive interface

Users can design analysis pipeline models and automate analysis tasks by employing an easy-to-use component programming interface irrespective of analysis bottlenecks or resource constraints. Providing open analysis pipelines and programs lowers the barrier to genomic big data analysis, enabling effective and efficient data analysis. Furthermore, algorithms that can be applied to big data sets are provided to enhance accessibility to big data analysis, and flexibility with respect to developing the desired user-defined algorithms is supported through a built-in Python, Bash, R development environment.

Open pipline/program approach

By disclosing and sharing new technologies to keep up with rapidly evolving and diversifying technologies, cutting-edge technology for genomic data analysis is maintained, active communication with researchers is supported, and access to collaborative environments and analysis technologies in the field of genomic data analysis is maximized.

Bio-Express system provides

Bio-Express (cloud-based open integrated analytics system)MORE

WORKBENCH and the GBOX and GBOX-CLI open analysis software platform helps to maximize the automation and management control efficiency for the analysis of a large volume of genomic data, and to make it more convenient to develop and maintain genomic data analysis. In addition, in order to support workflow development and genomic data analysis activities even in a poor computing environment, accessibility and analytical research production activities have been improved through the web service pipeline model design service so that large volumes of genomic data can be uploaded and analysis pipelines can be designed and run via Bio-Express web services.

Features of Bio-Express

Automated platform utilization service is provided by developing automated processing technology of the integrated analysis pipeline for big data analysis in the field of science and technology. Bio-Express provides a running environment based on the latest big data platform to provide an optimal analysis environment for various big data analyses, such as quick data processing and machine learning.

Support for the development of cloud-based analysis workflow

Workbench provides a highly and freely scalable workflow development environment that runs in a cloud environment. It also uses and learns big data and provides automation machines for the scientification of analysis workflow pipeline services. Automated analysis workflows can be developed using various analysis algorithms provided, and the development and execution environment for high-performance hybrid analysis pipelines is provided using big data analysis technology.

High-performance infrastructure-based big data service in the science field

Efficient data analysis, such as big data collection, segmentation, analysis, and visibility, is available based on proven analysis pipelines. Data analysis can be performed easily and simply through segmented analysis pipelines instead of the conventional complex code-based prediction system.

GBox, a system for the high-speed transfer of big data in the field of science

GBox supports the transfer of big data regardless of file size, format, transmission distance, or network conditions. It provides functions for fast backup and the automatic replication of big data consisting of several millions of individual files or large-scale data sets. It also provides a security layer for data transfer by using high-quality security technology for high-speed transmission.

Bio-Express infrastructure supports the analysis of large volumes of big data.

Bio-Express infrastructure information
Classification Resource(total) Specifications
Compute Nodes CPU : 1,188cores
  • - Cores : 36(cores/node)
  • - GPU : A100 X 4
  • - big memory Server : 12TB
Nodes : 33EA
MEM : 12.4 TB
STORAGE Capacity : 15PiB Large capacity high-speed storage
- File system : Lustre
interconnect network infiniBand Mellanox ConnectX-6 200Gbps
  • CPU when performing an analysis : 6core
  • Memory: 64GB available

When utilizing the maximum resources for each task
200 cases can be analyzed simultaneously