Javier E. Flores

This study evaluates plasma extracellular vesicle proteomics for identifying predictive biomarkers of type 1 diabetes development, finding 448 differentially abundant proteins and a 0.81 AUC in predicting islet autoimmunity.

This paper benchmarks feature screening methods for omics data classification, finding BcorSIS to be the most effective and efficient across various datasets.

This study shows that proinflammatory stress in beta cells increases ceramide-enriched extracellular vesicles via nSMase2, which may affect paracrine signaling in diabetes.

This study evaluates and refines assumptions in retention index scores for GC-MS metabolite identification to improve accuracy and reduce manual verification.

This paper improves false discovery rate estimation in GC-MS metabolomics by extending Gaussian mixture models to incorporate similarity scores and experimental data.