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WASAI 閃電測試賬戶註冊

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Download the full whitepaper to explore how WASAI and Advantech are driving innovation in genomic research, enhancing workflow efficiency, and paving the way for the future of precision medicine.

Introduction:

  • Next-Generation Sequencing (NGS) Revolution: Explore how NGS is transforming DNA sequencing, generating vast amounts of genomic data.

  • Challenges in Genomic Data Processing: Understand the hurdles in maintaining accuracy and efficiency in handling extensive raw data during secondary analysis.
     

Key Challenges:

  • High-Performance Computing Demand: The exponential growth in genomic data requires robust HPC solutions.

  • Data Management Issues: Discover the complexities of managing and analyzing vast genomic datasets.
     

Innovative Solution:

  • WASAI-Lightning Bio-IT Platform: Learn about this platform’s advanced capabilities, employing Agilex-based FPGA cards for efficient genomic analysis.

  • Advantech’s High-Performance Servers: Explore the powerful SKY-820V3, SKY-620V3, and SKY-8234D servers, optimized for computationally demanding tasks.
     

Case Studies:

  • Yonsei University Mirae Campus: See how this South Korean institution leverages the platform for disease research and AI-driven medical projects..

  • National Taiwan University College of Medicine: Understand how Taiwanese researchers use this technology for large population cohort studies.
     

Performance and Validation:

  • Speed and Accuracy: WASAI’s platform accelerates genome sequencing and maintains a high accuracy rate, revolutionizing secondary analysis.

  • Efficiency Gains: Realize the significant performance improvements, reducing genome sequencing time from 30 hours to just 3 hours.
     

Conclusion:

  • ​Future of Genomic Analytics: Embrace the potential of hardware acceleration in advancing precision medicine, offering faster and more accurate genomic analysis.

  • Why Choose Advantech and WASAI: Discover the benefits of this collaborative solution, providing scalable, flexible, and cost-effective genomic analysis.
     

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