Multiomix

Multiomix integrates and analyzes multi-omics data to identify correlations between mRNA expression and non-mRNA genomic features and to assess prognostic implications of genomic and epigenomic events.

Key Features:

• Data Integration and Analysis: Integrates multi-omics data from public functional genomic databases and user-uploaded datasets and provides functions and pipelines for comprehensive analysis.
• Correlation Identification: Identifies significant correlations between mRNA expression and non-mRNA genomic features such as miRNAs, DNA methylation patterns, and copy number variations (CNVs) across the genome.
• Sequence-Based Interaction Prediction: Predicts sequence-based interactions, including miRNA-mRNA relationships, to elucidate post-transcriptional regulation.
• Prognostic Value Assessment: Evaluates prognostic implications of identified genomic and epigenomic events to inform clinical decision-making and personalized medicine approaches.
• Analytical Pipelines and Scalability: Implements analytical pipelines and algorithms designed to handle large-scale multi-omics datasets.

Scientific Applications:

• Biomarker Discovery: Identifies potential biomarkers for diagnosis, prognosis, and therapeutic targeting by analyzing the interplay of genetic mutations, epigenetic modifications, and gene expression changes.
• Cancer Biology and Precision Oncology: Integrates diverse datasets to uncover insights into cancer biology and to support precision oncology research.

Methodology:

Aggregates multi-omics data and applies analytical pipelines and algorithms to identify significant genomic and epigenomic events associated with gene expression modulation, designed for large-scale datasets.