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Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management

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Published on: November 30, 2022

Translational biomedical informatics in the cloud: present and future.

Jiajia Chen¹, Fuliang Qian, Wenying Yan

¹Center for Systems Biology, Soochow University, Suzhou 215006, China.

Biomed Research International

|April 16, 2013

Summary

Cloud computing offers a powerful solution for managing the vast amounts of molecular and clinical data generated by high-throughput sequencing. This approach facilitates translational bioinformatics research by addressing big data challenges in data mining, storage, and integration.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Recent decades have seen an exponential increase in publicly available molecular and clinical data due to advances in high-throughput experimental techniques.
This data surge has paved the way for translational bioinformatics, aiming to bridge biological discoveries with clinical applications.
However, the sheer scale and complexity of this data present significant hurdles for effective data mining, storage, and integration.

Purpose of the Study:

To demonstrate the utility and potential of cloud computing in addressing the challenges posed by big data in translational bioinformatics.
To present a vision for cloud computing as a key enabler for future translational bioinformatics research.

Main Methods:

The study discusses the application of cloud computing principles and platforms.
It focuses on addressing the "big data" problems inherent in large-scale molecular and clinical datasets.
The approach involves leveraging cloud infrastructure for data management and analysis.

Main Results:

Cloud computing demonstrates significant utility in managing and processing large-scale, high-dimensional molecular and clinical data.
The proposed cloud-based solutions effectively tackle challenges in data mining, storage, and integration.
The findings highlight the practical benefits and promise of cloud computing for the field.

Conclusions:

Cloud computing is a crucial tool for overcoming the "big data" obstacles in translational bioinformatics.
Adopting cloud computing can significantly facilitate and accelerate translational bioinformatics research.
The future of translational bioinformatics is strongly linked to the effective utilization of cloud infrastructure.