Clinical proteomics and disease signature analysis in Spain

As a Data Analyst Bioinformatician at the Institute for Health Science Research Germans Trias i Pujol in Spain, I worked with OLINK proteomic data and clinical phenotypes to study stress-related signaling pathways in cancer and inflammatory disease.

My work included developing and validating Random Forest and linear mixed models in R and Python to classify disease states with more than 85% accuracy.

I performed differential expression and pathway analyses, identifying immune and oxidative stress-associated signatures linked to disease resolution and progression.

The role also included sex-specific proteomic response analysis, publication-quality figures, manuscript co-authorship, and communication of biomedical findings for peer-reviewed research.