BioVLAB-MMIA-NGS: microRNA-mRNA integrated analysis using high-throughput sequencing data

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• MicroRNAs (miRNAs) are crucial regulators of gene expression.
• Predicting miRNA targets genome-wide is computationally challenging.
• Integrated miRNA-mRNA analysis requires advanced bioinformatics systems.

Purpose of the Study:

• To enhance the existing mRNA-miRNA Integrated Analysis (MMIA) web server.
• To adapt the server for high-throughput next-generation sequencing (NGS) data.
• To deploy the improved server on cloud and high-performance computing platforms.

Main Methods:

• Developed BioVLAB-MMIA-NGS, a new version of the MMIA web server.
• Integrated various bioinformatics tools and databases for NGS data analysis.
• Deployed the server on Amazon cloud and the MAHA high-performance server.

Main Results:

• BioVLAB-MMIA-NGS accurately determines miRNA expression levels from NGS data.
• The system facilitates the detection of potential novel miRNAs.
• Accurate identification of many-to-many relationships between miRNAs and target genes is achieved.

Conclusions:

• BioVLAB-MMIA-NGS provides a powerful and accurate platform for integrated miRNA-mRNA analysis.
• The enhanced server supports high-throughput sequencing data, advancing miRNA target prediction.
• This tool addresses the computational challenges in miRNA-mRNA interaction studies.