A review of Cloud computing technologies for comprehensive microRNA analyses.

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Cloud computing provides scalable computational resources and services.
• MicroRNA analysis, particularly with next-generation sequencing data, demands significant storage and distributed computing power.
• Current utilization of cloud platforms for microRNA analysis is limited but shows potential for growth.

Purpose of the Study:

• To identify beneficial cloud computing properties and service models for microRNA analysis.
• To outline key cloud services applicable to microRNA research.
• To review existing microRNA analysis solutions and assess cloud adoption.

Main Methods:

• Review of cloud computing properties and service models relevant to bioinformatics.
• Identification and explanation of cloud services (storage, computation, web hosting, machine learning, Big Data frameworks) applicable to microRNA analysis.
• Survey of current microRNA analysis tools and platforms.

Main Results:

• Specific cloud properties and service models are highly beneficial for microRNA analysis.
• Key cloud services like scalable storage, computational power, and Big Data frameworks can significantly aid microRNA research.
• The adoption of cloud computing in microRNA analysis is currently low.

Conclusions:

• Cloud computing offers substantial advantages for microRNA analysis, particularly for handling large-scale genomic data.
• Increased awareness of cloud applicability is expected to drive future adoption in microRNA research.
• Leveraging cloud services can optimize microRNA data processing and analysis efficiency.