Sheng Li

Associate Professor of Cancer Biology and Quantitative and Computational Biology

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

Websites

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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

Transcriptional heterogeneity predicts and enables clonal selection in ageing haematopoiesis. Res Sq. 2026 Jun 25.. View in PubMed
Hematopoietic stem cell aging promotes TET2 clonal hematopoiesis. Res Sq. 2026 Feb 09.. View in PubMed
Tet2 deficiency promotes IgG1+ B-cell expansion and differentiation blockade through deregulation of the Nfkbia-c-Rel axis. Hemasphere. 2026 Jan; 10(1):e70296.. View in PubMed
Advancing biological understanding of cellular senescence with computational multiomics. Nat Genet. 2025 Oct; 57(10):2381-2394.. View in PubMed
NANOME: A Nextflow pipeline for haplotype-aware allele-specific consensus DNA methylation detection by nanopore long-read sequencing. bioRxiv. 2025 Jul 04.. View in PubMed
Inferring single-cell spatial gene expression with tissue morphology via explainable deep learning. bioRxiv. 2025 Jun 02.. View in PubMed
MorPhiC Consortium: towards functional characterization of all human genes. Nature. 2025 02; 638(8050):351-359.. View in PubMed
Quantifying interpretation reproducibility in Vision Transformer models with TAVAC. Sci Adv. 2024 12 20; 10(51):eabg0264.. View in PubMed
Intermittent clearance of p21-highly-expressing cells extends lifespan and confers sustained benefits to health and physical function. Cell Metab. 2024 Aug 06; 36(8):1795-1805.e6.. View in PubMed
Causal network perturbation analysis identifies known and novel type-2 diabetes driver genes. bioRxiv. 2024 May 26.. View in PubMed