FunSys

FunSys integrates differential expression data from RNAseq and proteomics to identify correlations between transcriptomic and proteomic changes in NGS-derived datasets.

Key Features:

• Integration of RNAseq and proteomics: Correlates differential expression patterns between RNAseq-derived transcriptomes and proteomic datasets to link mRNA and protein level changes.
• Differential expression analysis: Evaluates differential expression patterns across conditions using RNAseq and proteomics inputs to detect significant transcriptomic and proteomic changes.
• Visualization and reporting: Generates charts and reports summarizing integrated analysis results to aid interpretation of transcript–protein relationships.

Scientific Applications:

• Gene expression analysis: Investigates differential gene expression at the transcript and protein levels to study regulatory mechanisms.
• Proteogenomics: Supports proteogenomic studies by correlating transcriptomic and proteomic data to assess how genetic variation influences protein expression.
• Systems biology: Integrates multi-omics expression data to inform models of cellular processes and system-level responses.

Methodology:

Processes and analyzes large-scale RNAseq and proteomics datasets with computational algorithms and evaluates differential expression patterns to identify transcriptomic–proteomic correlations.