MAGINE

MAGINE integrates quantitative multi-omics time-course datasets (e.g., RNA sequencing and label-free proteomics) to generate mechanistic hypotheses about signaling and cellular fate processes.

Key Features:

• Multi-Omics Data Handling: Manages and analyzes quantitative multi-omics datasets across multiple samples and time points, including RNA sequencing and label-free proteomics.
• Data Management and Integration: Implements data management and integration for large-scale multi-condition transcriptome and proteome time-course datasets.
• Enrichment Analysis: Performs enrichment analysis to identify significant biological processes and pathways within datasets.
• Biological Network Construction: Constructs biological networks representing interactions among biochemical species for systems-level analysis.
• Visualization Methods: Produces visualization outputs to interpret and present dynamic cellular response data.

Scientific Applications:

• HL-60 bendamustine response: Analysis of HL-60 cell responses to bendamustine, yielding mechanistic hypotheses that link DNA damage response, cell cycle arrest, and apoptosis across >2000 biochemical species.
• Discovery of non-canonical treatment effects: Identification of unexpected pathway disruptions, such as perturbation of cellular pathways relevant to HIV infection by bendamustine.

Methodology:

Computational steps explicitly include data management, enrichment analysis, biological network construction, and visualization to integrate quantitative multi-omics time-course datasets.