Advised a data science team on the identification of prognostic gene signatures for the development of RT-qPCR–based biomarkers in fibrotic disease. The work combined weighted gene regulatory network analysis with differential expression and gene set enrichment approaches applied to bulk and single-cell multi-omics datasets to support the development of targeted therapeutic strategies.

Advised a team of data analysts on the design, optimization, and validation of computational analyses for a study investigating two RNA-based drug treatments. Guidance included selecting appropriate statistical and bioinformatics workflows, improving analysis robustness, and ensuring results were reproducible and biologically meaningful. The work supported reliable interpretation of treatment effects and strengthened the analytical foundation of the study’s findings.

Provided expert guidance on the computational analysis of high-throughput sequencing data. Supported teams in designing robust bioinformatics workflows for data processing, quality control, and downstream interpretation. The consulting focused on ensuring reliable results, efficient data handling, and the appropriate application of state-of-the-art analytical methods.