Summary
Yuliang Tan is a computational biologist and Associate Project Scientist with 12 years of hands-on experience translating chromatin biology into mechanistic and therapeutically relevant insights. Based at UC San Diego, he designs and implements integrated experimental-computational pipelines for ATAC-seq, ChIP-seq, CUT&RUN, PRO-seq and large-scale multi-omics, and has driven projects that reveal how enhancer methylation and TOP1-linked complexes control signal-dependent gene expression. His work, published in top journals such as Nature, Cell and Molecular Cell, blends genome-wide assays with CRISPR perturbations, in vivo models, and machine learning–driven predictive modeling. He routinely leads cross-disciplinary teams, builds custom bioinformatics tools (HOMER/BEDTools workflows and bespoke pipelines), and moves discoveries from mechanistic mapping toward therapeutic hypotheses. Notably, he uncovered enhancer demethylation as a critical mediator of stimulus-responsive transcription and mapped TOP1cc genome-wide to interrogate enhancer activation. Fluent in R and Python, he mentors junior scientists to bridge wet-lab and computational approaches.
12 years of coding experience
16 years of employment as a software developer
Bachelor's degree, Biology, General, Bachelor's degree, Biology, General at Lanzhou University
Doctor of Philosophy - PhD, Bioinformatics, and Computational Biology, Doctor of Philosophy - PhD, Bioinformatics, and Computational Biology at Chinese Academy of Sciences
English, Chinese