mESAdb

mESAdb performs multivariate analysis of mature microRNA sequences and expression profiles to enable exploration of mature microRNA sequences, target data, and selected expression datasets from human, mouse, and zebrafish.

Key Features:

• Implementation and architecture: Implemented in PHP and JavaScript with a modular architecture that enables integration with R-based analysis.
• R integration: Integrates with existing R packages for statistical analysis and visualization of expression data.
• Mining of microRNA expression data: Extracts subsets of microRNAs either manually or based on sequence motifs.
• Pair-wise multivariate analysis: Performs pair-wise multivariate comparative analysis of expression datasets within a single taxon and between taxa (human, mouse, zebrafish).
• Annotation linkage: Links microRNA subsets to annotation resources including HUGE Navigator, KEGG, and GO.
• Extensibility: Supports incorporation of additional datasets and R-based analytical tools.
• User data input: Accepts user-uploaded datasets for analysis.

Scientific Applications:

• Expression mining: Identification and extraction of microRNA subsets by manual selection or motif-based criteria.
• Comparative expression analysis: Comparative multivariate analysis of microRNA expression within and across human, mouse, and zebrafish datasets.
• Functional annotation: Functional interpretation of microRNA subsets via linkage to HUGE Navigator, KEGG, and GO.
• Target data exploration: Exploration of mature microRNA sequences and associated target data.
• Cross-taxa comparison: Cross-taxa comparison of microRNA expression patterns between human, mouse, and zebrafish.

Methodology:

Computational methods include extraction of microRNA subsets manually or by motif, pair-wise multivariate analysis of expression datasets, linkage of subsets to HUGE Navigator, KEGG, and GO, and integration with R packages; the system is implemented in PHP and JavaScript.