Daniel Tan
Daniel Tan
Master of Biomedical Informatics, Class of 2022

During his undergraduate years, Daniel harnessed machine learning and big omics data to investigate intertumoral heterogeneity in pancreatic adenocarcinoma through the lens of alternative splicing. He has also previously worked for the UCLA Metabolomics Center, contributing to the development of software for downstream quality control, analysis, and visualization of mass spectrometry data. Daniel's research interests are in cancer omics, pharmacology, translational bioinformatics, and machine learning.

Previous Education

BS, Molecular, Cell, and Developmental Biology - University of California, Los Angeles