Sheng Li, Ph.D.
Associate Professor
Applies data integration and machine learning to advance the frontiers of cancer epigenomics and evolution.
My research interest is to understand the inner workings of cancer cells – the genetic and epigenetic heterogeneity that drive cancer initiation and progression. We utilize computational and sequencing methodologies to identify and characterize the essential epigenetic lesions that guide cancer cells to evolve and escape from anti-cancer therapy. The ultimate goal is to develop novel methods to predict and address tumor evolution.
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Profile StoryNovember 09, 2021Using next-gen technology to explore how aging raises the risk for leukemia
JAX's Sheng Li is exploring how aging raises the risk for leukemia, and works to improve cutting edge tools for data analysis. -
Research HighlightJune 17, 2020New research reveals the role of epigenetic dysfunction in blood cancer
A new discovery by JAX cancer researcher Sheng Li points to the possibility of new lymphoma treatments that would restore the protective effect of TET2 in tumors where it has been mutated.
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Research HighlightJanuary 18, 2021JAX uses genetic models to fight CUP
A JAX team developed CUP-AI-Dx, a machine learning tool that uses RNA sequence data for analysis. The researchers show that CUP-AI-Dx provides an important clinical tool to help guide therapies for CUP patients.