Sheng Li Lab for Computational Biology
@The Jackson Laboratory for Genomic Medicine

About the Principal Investigator

                                      Sheng Li received her PhD in Computational Biology from Cornell University in 2014.                                        She is now an Associate Professor at The Jackson Laboratory (JAX) and a member                                          of its NCI-designated Cancer Center. She is a recipient of the “NextGen Star” from                                            The American Association for Cancer Research in 2020 and the Maximizing                                                      Investigators' Research Award from NIH-NIGMS. As a Computational Biologist, Li                                              leverages machine learning algorithms to identify critical ‘epigenetic’ modifications in                                        the chromosomes that can drive blood cancer development by changing the                                                    expression of key genes. She has developed novel, open-source software that                                                  enables other researchers to conduct their own studies of blood malignancies.

​

Research interests

Our ongoing research lays a conceptual and technological foundation for transformative advances in blood cancer therapy, by revealing the inner workings of cancer cells – especially the epigenetic plasticity and heterogeneity that drive cancer initiation and progression – in the context of aging.

        We are leveraging: i) unique insights into the epigenetic mechanisms controlling hematopoietic stem cells aging and hematopoietic malignancies, ii) powerful and cutting-edge genome technologies and computational algorithms that I developed for studying epigenetic plasticity and heterogeneity, iii) aged genetically engineered mouse models. Building on the important prior research discoveries and on new interdisciplinary collaborations, we have set three main research areas: 

1. Single-cell multi-omics: We will elucidate how aging and clonal hematopoiesis influence the propensity of blood stem cells to adapt to altered environments (“evolvability”) via single-cell multi-omics, which could not only forge a new paradigm for our understanding of leukemia onset but also provide candidate pathways for the development of preventative interventions

2. 3D epigenomics: We will systematically define the key epigenomics and 3D genomics features of mutated blood stem cells that change with age. This study will support the development of new therapies to prevent blood stem cell over-proliferation and thereby improve the healthspan of aging individuals.

3. Long-read sequencing: We are developing a computational framework for integrative analysis of epigenomics data including nanopore sequencing data that will decipher the cell fate decisions during stem cell differentiation and cancer via advanced deep learning algorithms and statistical methods

​

Recent news

1. Sheng served as a reviewer for NIH/NCI’s Innovative Molecular Analysis Technologies program

2. Our paper DNA methylation-calling tools for Oxford Nanopore sequencing: a survey and human epigenome-wide evaluation has been published in Genome Biology

3. We received an U01 grant together with Dr. James DeGregori from NIH/NCI

4. Our paper CUP-AI-Dx: A tool for inferring cancer tissue of origin and molecular subtype using RNA gene-expression data and artificial intelligence has been highlighted as the best paper of oncology in Commentary 2020: A year to remember at EBioMedicine

5. Our paper Somatic mutations drive specific, but reversible epigenetic heterogeneity states in AML has been published in Cancer Discovery

6. Sheng joined the editorial board as an Associate Editor of Science Advances.

Follow us