Eric Londin

Eric Londin serves as an Assistant Professor at the Computational Medicine Center within the Sidney Kimmel Medical College at Thomas Jefferson University. He concurrently directs the Computational Biology & Medicine MS Program, positioning him at the nexus of academic leadership and translational research.

Dr. Londin's research program centers on the comprehensive characterization of microRNAs (miRNAs) and other small non-coding RNAs in human disease pathogenesis. His laboratory employs integrated computational and molecular biology approaches to investigate:

• The complete catalog of miRNAs and their isoforms (isomiRs) in the genome
• The composition and variation of miRNAs across disease states and populations
• The target genes and regulatory mechanisms of miRNAs
• The role of miRNAs and tRNA-derived fragments in cancer (particularly melanoma and pancreatic cancer) and neurodegenerative disorders (ALS, Parkinson's)
• The contribution of non-coding RNA heterogeneity to health disparities across race, gender, and populations

Analysis of his 2021-2025 publications reveals three dominant research trajectories: (1) Development of computational tools like IsoMiRmap for exhaustive isomiR mining from RNA-seq data; (2) Discovery of novel RNA biomarkers for diagnostic and prognostic applications across uveal melanoma, pancreatic cancer, and neurological disorders; (3) Investigation of how non-coding RNA expression variations contribute to disease heterogeneity and health disparities, particularly in triple-negative breast cancer and prostate cancer. His work consistently bridges algorithm development with clinical validation of RNA biomarkers.

As Director of the Computational Biology & Medicine MS Program, Dr. Londin leads an interdisciplinary educational initiative training students in genomic data analysis and translational applications. His research group functions as a collaborative hub integrating bioinformatics expertise with clinical oncology and neuroscience research at Thomas Jefferson University, with strong emphasis on translating non-coding RNA discoveries into precision medicine applications.