BioVLAB-MMIA-NGS – MicroRNA-mRNA Integrated Analysis using High Throughput Sequencing Data

It is now well established that microRNAs (miRNAs) play a critical role in regulating gene expression in a sequence specific manner and genome-wide efforts are underway to predict known and novel miRNA targets. However, the integrated miRNA-mRNA analysis remains a major computational challenge, requiring powerful informatics systems and bioinformatics expertise.

The objective of this study was to modify a widely recognized web server for the integrated mRNA-miRNA analysis (MMIA) and its subsequent deployment on the Amazon cloud (BioVLAB-MMIA) in order to be compatible with high throughput platforms, including next generation sequencing data (e.g., RNA-seq).


Researchers at Indiana University Bloomington developed a new version called BioVLAB-MMIA-NGS, deployed on both Amazon cloud and on a high performance, publically available server called MAHA. By utilizing next generation sequencing (NGS) data and integrating various bioinformatics tools and databases, BioVLAB-MMIA-NGS offers several advantages.

  1. Sequencing data is more accurate than array-based methods for determining miRNA expression levels.
  2. Potential novel miRNAs can be detected by using various computational methods for characterizing miRNAs.
  3. Because miRNA-mediated gene regulation is due to hybridization of a miRNA to its target mRNA, sequencing data can be used to identify many-to-many relationship between miRNAs and target genes with high accuracy.



Chae H, Rhee S, Nephew KP, Kim S. (2014) BioVLAB-MMIA-NGS: MicroRNA-mRNA Integrated Analysis using High Throughput Sequencing Data. Bioinformatics. [Epub ahead of print]. [abstract]