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

Heejoon Chae, Sungmin Rhee, Kenneth Nephew, Sun Kim

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

Motivation: 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. Results: The objective of this study was to modify our widely recognized Web server for the integrated mRNA-miRNA analysis (MMIA) and its subsequent deployment on the Amazon cloud (BioVLABMMIA) to be compatible with high-throughput platforms, including next-generation sequencing (NGS) data (e.g. RNA-seq). We developed a new version called the BioVLAB-MMIA-NGS, deployed on both Amazon cloud and on a high-performance publicly available server called MAHA. By using NGS data and integrating various bioinformatics tools and databases, BioVLAB-MMIA-NGS offers several advantages. First, sequencing data is more accurate than array-based methods for determining miRNA expression levels. Second, potential novel miRNAs can be detected by using various computational methods for characterizing miRNAs. Third, because miRNA-mediated gene regulation is due to hybridization of an miRNA to its target mRNA, sequencing data can be used to identify many-to-many relationship between miRNAs and target genes with high accuracy.

Original languageEnglish
Pages (from-to)265-267
Number of pages3
JournalBioinformatics
Volume31
Issue number2
DOIs
StatePublished - Jan 15 2015

Fingerprint

MicroRNA
MicroRNAs
Messenger RNA
Sequencing
High Throughput
Throughput
Bioinformatics
Gene expression
Servers
Genes
Computational methods
RNA
Computational Biology
Target
Many to many
Informatics
Gene Regulation
Web Server
Expertise
Computational Methods

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computational Mathematics
  • Statistics and Probability
  • Medicine(all)

Cite this

BioVLAB-MMIA-NGS : MicroRNA-mRNA integrated analysis using high-throughput sequencing data. / Chae, Heejoon; Rhee, Sungmin; Nephew, Kenneth; Kim, Sun.

In: Bioinformatics, Vol. 31, No. 2, 15.01.2015, p. 265-267.

Research output: Contribution to journalArticle

Chae, Heejoon ; Rhee, Sungmin ; Nephew, Kenneth ; Kim, Sun. / BioVLAB-MMIA-NGS : MicroRNA-mRNA integrated analysis using high-throughput sequencing data. In: Bioinformatics. 2015 ; Vol. 31, No. 2. pp. 265-267.
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