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Related Experiment Video

Updated: May 18, 2026

An Experimental and Bioinformatics Protocol for RNA-seq Analyses of Photoperiodic Diapause in the Asian Tiger Mosquito, Aedes albopictus

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Published on: November 30, 2014

Microbase2.0: a generic framework for computationally intensive bioinformatics workflows in the cloud.

Keith Flanagan¹, Sirintra Nakjang, Jennifer Hallinan

¹School of Computing Science, Newcastle University, Newcastle upon Tyne, UK.

Journal of Integrative Bioinformatics

|September 25, 2012

Summary

This summary is machine-generated.

Bioinformatics data analysis requires robust infrastructure. Microbase2.0 leverages Grid and Cloud computing for high-throughput data, enabling large-scale protein localization studies.

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Area of Science:

Bioinformatics
Computational Biology
Distributed Computing

Background:

Increasingly large bioinformatics datasets and complex analyses necessitate advanced data handling infrastructures.
Grid and Cloud technologies offer solutions for the computational demands of high-throughput data analysis.

Purpose of the Study:

To present an approach for developing and executing bioinformatics applications on Grid and Cloud infrastructures.
To introduce Microbase2.0, a framework for running applications using distributed computing resources.

Main Methods:

Developed a framework, Microbase2.0, for executing applications on Grid and Cloud technologies.
Created an automated Cloud-based bioinformatics workflow utilizing Microbase2.0.
Deployed the workflow across multiple Amazon EC2 data centers and a university Condor Grid.

Main Results:

Executed several CPU years of computational work in under two months.
Generated a comprehensive dataset characterizing the cellular localization of over 3 million proteins.
Covered 867 taxa, including bacteria, archaea, and unicellular eukaryotes.

Conclusions:

Microbase2.0 provides an effective platform for large-scale bioinformatics analyses using distributed computing.
The framework successfully enabled rapid characterization of protein localization across a wide range of taxa.
Microbase2.0 is publicly available, promoting further research in computational biology.