Our team

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Wanding Zhou

Assistant Professor of Pathology and Lab Medicine

PhD in Bioengineering at Rice U.
Postdoc in MD Anderson Cancer Center and Van Andel Institute.
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Sol Moe Lee

Postdoctoral Fellow
11/2020-

Ph.D. in Bioinformatics in 2020
Seoul National University
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David Goldberg

Graduate Student
12/2021-

UPenn Neuroscience Graduate Group
matric year: 09/2020
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Diljeet Kaur

Graduate Student
05/2022-

UPenn CAMB/GE Group
matric year: 09/2021
Co-supervised with Ziyue Gao.
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Wonder (Heqiao) Zhu

Graduate Student
09/2022-

UPenn BE graduate group
matric year: 09/2022
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Cameron Cloud

Research Technician
07/2023-

BS in Biology, Biotechnology
Lafayette College


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Hongxiang Fu

Graduate Student
09/2023-

UPenn BE graduate group
matric year: 09/2023


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Yunjun Kang

Graduate Student
09/2023-

UPenn BE graduate group
matric year: 09/2023


Alumni

  • Waleed Iqbal (09/2021-11/2022): last known position: grad student at Drexel University (Alessandro Fatatis lab)
  • Wubin Ding (10/2021-04/2023): Last known position: Postdoc at Salk Institute (Joe Ecker lab)
  • Ethan Moyer: undergraduate research associate. Last known position: Moberg Analytics.
  • Andrew Patterson (06/2021-08/2021): GCB rotation graduate student.
  • Yang Wan (01/2020-10/2021): intern master student. Now at University of Pennsylvania.
  • Borui Xiao (01/2020-03/2020): intern master student. Now at Hengrui Medicine Inc.

Join Us & Our Science!

Rotation Projects

1. DNA methylation-based computational decoding of differentiation and mitotic aging trajectory in human and mouse. Through this project, we hope to advance the understanding of the establishment of epigenetic cell identity and the progression of cellular aging using integrative modeling. We will investigate the quantitative contribution of epigenetic and genetic factors that jointly determine chromatin state evolution at different stages of organismal development.

2. Developing advanced informatics for Infinium DNA methylation BeadChip for mice. In collaboration with Illumina Inc and FOXO Biosciences, this project aims to comprehensively characterize this new assay platform that queries DNA methylation in mice. Students will develop a deep understanding of the Infinium BeadChip technology and co-author R/Bioconductor software while gaining experience in mouse genetics, epigenetics, and different mouse models for human disease.

3. Understanding tissue-specific mitotic turnover using long-read sequencing technology. The project leverages burgeoning long-read genomic profiling techniques to study different epigenetic factors that collectively govern stem cell turnover and cellular aging in single-cell resolution. In collaboration with bench scientists in the lab, we hope to resolve the long-standing puzzle of heterogeneity in the mitotic clock and its implication to cancer biology.

4. Informatics for cell type inference and rare cell type discovery using DNA methylation. We are developing an iterative learning framework and cell type assignment system by applying factor analysis to DNA methylome data. We will leverage the wealth of available single-cell and sorted tissue DNA methylome to reconstruct the spatial and temporal cell composition panorama for human tissue. The project aims to build out a comprehensive intelligent machine system that infers epigenetic cell identity through large-scale public data deconvolution and integration.

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AI for DNA Methylation

We create inference methods to let DNA methylation data inform cell-of-origin, pathology, cellular aging, and environmental purturbations.
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Diagnostic Cell-free DNA Methylation

We develop informatics to enhance the power of DNA methylation-based liquid biopsy technologies for cancer diagnosis of the next generation.
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Reconstructing Epigenetic Tree of Differentiation

Reconstructing the history of cell differentiation is the holy grail of developmental biology. We are leveraging DNA methylation as a surrogate of epigenetic cell identity and approach this very central question.
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Long-read sequencing-based DNA modification

Long-read sequencing technologies are transforming how people study epigenetics. We use them to unveil the epigenetic mechanism of human development and disease progression.