Riya Singh

Research Intern @Genyo. Pfizer-University Of Granada-Junta De Andalucia Center For Genomics And Oncological Research

Granada, ES

I worked at the intersection of bioinformatics, machine learning, and clinical research, focusing on extracting meaningful insights from complex biomedical data. My recent work involved cleaning and imputing clinical and genomic datasets (using missForest) to ensure quality and consistency, conducting exploratory and mutation profile analysis with maftools, and building machine learning models (Random Forest, SVM, Elastic Net) to predict cancer prognosis. I also applied feature selection and SHAP values to enhance model interpretability and highlight clinically relevant biomarkers.As part of my research project, I developed a bioinformatics pipeline to study VHL and EPAS1 gene variants as potential biomarkers of aggressiveness in clear cell renal cell carcinoma (ccRCC). By integrating genetic algorithms, recursive feature elimination, and SVM classifiers, I identified key SNPs associated with late-stage cancers and demonstrated the feasibility of combining genomic and clinical data for prognosis modeling.