M IA

M IA performs comprehensive analysis of DNA microarray data to support gene expression studies, including raw data processing, differential expression analysis, reconstruction of gene interaction networks, and compliance with MIAME.

Key Features:

• Integrated workflow: Handles raw data storage and processing through to identification of differentially regulated genes and downstream analysis.
• MIAME compliance: Maintains metadata and data handling in accordance with the Minimum Information About a Microarray Experiment (MIAME) standard.
• Gene network reconstruction: Reconstructs gene interaction networks by integrating microarray data with ontologies, metabolic and signaling pathways, protein interactions, miRNA associations, and transcription factor links.
• Automatic gene annotation: Annotates genes automatically by mapping to multiple biological databases to support functional interpretation.
• Graphical visualization: Provides graphical methods for visualization and analysis of gene interaction networks.
• Statistical methods: Applies robust statistical techniques for microarray data analysis and assessment of significance.

Scientific Applications:

• Pathway and mechanism discovery: Integration of differential gene expression with biological knowledge to identify molecular interaction networks underlying biological processes.
• Disease-associated network identification: Enables identification of novel molecular networks associated with disease, as demonstrated on liver tissue microarray data identifying networks related to fibrogenesis.

Methodology:

Built on a flexible modular architecture enabling customization and scalability; includes integration of microarray data with ontologies, metabolic and signaling pathways, protein interactions, miRNA associations, and transcription factor links, automatic gene annotation from biological databases, application of statistical techniques, and graphical network visualization.