Sheng Li

Associate Professor of Cancer Biology and Quantitative and Computational Biology

Co-leader of the Epigenetic Regulation in Cancer (ERC) Program

Websites

Is this your profile? Click to edit

Overview

Dr. Sheng Li’s lab develops AI-driven multi-omics approaches to investigate how aging and somatic mutations reshape hematopoietic stem cells, driving clonal hematopoiesis and leukemia.
By integrating single-cell, spatial, and long-read sequencing, we uncover how epigenetic and transcriptional programs influence stem-cell aging and cancer evolution.
Our interdisciplinary team combines computational biology and translational genomics to transform large-scale data into actionable insights that advance precision medicine and improve human health.

Awards

Leukemia & Lymphoma Society: Career Development Program Scholar Award, 2024
– 2029
University of Colorado NCI-designated Comprehensive Cancer Center: Cancer Warrior Award, 2023
The Jackson Laboratory: Faculty Milestone Award, 2022
American Association for Cancer Research: NextGen Star, 2020
National Institute of General Medical Sciences: Maximizing Investigators’ Research Award, 2019
– 2024
Leukemia Research Foundation: New Investigator Award, 2017
WorldQuant Foundation: WorldQuant Scholar, 2015
National Science Foundation: RECOMB-seq Travel Fellowship, 2013

Research Funding

Computational interrogation of Epigenetic Regulation in Cellular Plasticity and Heterogeneity
NIH · R35GM162228 · May 1, 2026 – Jan 31, 2031 · Role: Principal Investigator
Multi-omic phenotyping of human transcriptional regulators
NIH · U01HG013175 · Sep 11, 2023 – Jul 31, 2028 · Role: Principal Investigator
3D Genome Reorganization and Epigenome Dynamics of Clonal Hematopoiesis
NIH · R56AG071766 · Sep 15, 2022 – Aug 31, 2023 · Role: Principal Investigator
Impact of aging and clonal hematopoiesis on epigenetic heterogeneity, evolvability, and leukemogenesis
NIH · U01CA271830 · Sep 23, 2021 – Aug 31, 2026 · Role: Principal Investigator
An Integrative Computational Framework for DNA Hydroxymethylation Data Mining and Interpretation
NIH · R35GM133562 · Aug 1, 2019 – Jul 31, 2024 · Role: Principal Investigator

Research Keywords

Computational Biology
Artificial Intelligence
Translational Epigenomics
Cancer Evolution
Aging

Media

Publications

Data-driven modeling of core gene regulatory network underlying leukemogenesis in IDH mutant AML. NPJ Syst Biol Appl. 2024 Apr 09; 10(1):38.. View in PubMed
Challenges and opportunities for modeling aging and cancer. Cancer Cell. 2023 04 10; 41(4):641-645.. View in PubMed
Inferring the Cancer Cellular Epigenome Heterogeneity via DNA Methylation Patterns. Cancer Treat Res. 2023; 190:375-393.. View in PubMed
NetAct: a computational platform to construct core transcription factor regulatory networks using gene activity. Genome Biol. 2022 12 27; 23(1):270.. View in PubMed
Interchromosomal interaction of homologous Stat92E alleles regulates transcriptional switch during stem-cell differentiation. Nat Commun. 2022 07 09; 13(1):3981.. View in PubMed
DNA methylation-calling tools for Oxford Nanopore sequencing: a survey and human epigenome-wide evaluation. Genome Biol. 2021 10 18; 22(1):295.. View in PubMed
Network Topology of Biological Aging and Geroscience-Guided Approaches to COVID-19. Front Aging. 2021 Jul; 2.. View in PubMed
epihet for intra-tumoral epigenetic heterogeneity analysis and visualization. Sci Rep. 2021 01 11; 11(1):376.. View in PubMed
Circulating miRNA Spaceflight Signature Reveals Targets for Countermeasure Development. Cell Rep. 2020 12 08; 33(10):108448.. View in PubMed
CUP-AI-Dx: A tool for inferring cancer tissue of origin and molecular subtype using RNA gene-expression data and artificial intelligence. EBioMedicine. 2020 Nov; 61:103030.. View in PubMed