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Computational Cancer Genomics

Bridging Computational Innovation and Cancer Biology

Our Mission

We develop machine learning approaches to explore the transcriptional heterogeneity and plasticity in cancer. Our research bridges computational innovation and cancer biology with a focus on chromatin, transcription, and cancer evolution under treatment.


Research Focus

Project 1

Multiscale models for DNA

Investigating effects of non-coding variants in cancer.

Project 2

Integration and representation learning

AI-driven integration of heterogeneous data for biomarker discovery.

Project 3

Deconvolution of tumor signals

Getting insights into tumor heterogeneity from bulk data.

Project 4

Multiomics survival models

Predicting patient outcome from multi-model data.



Highlighted Projects

Modeling Effects of Non-coding Variants

Predicting the effects of non-coding variants on chromatin accessibility and enhancer-promoter interactions. [ASAP, UniversalEPI]

Cancer-Specific Foundation Model

Developing a foundation model for single-cell transcriptomics in cancer. [CancerFoundation]

Discovery of Shared Transcriptional States

Evaluating methods for discovering common transcriptional states in tumors. [CanSig]

Tumor Cell States in EAC

Mapping transcriptional states in esophageal adenocarcinoma. [Cell Reports Medicine, 2025]

On Filtering Cells with High MT RNA in Cancer Studies

Showing that MT RNA-high cells in scRNA-seq are a viable, metabolically altered cell population. [Genome Biology, 2025]

DNA Methylation as a Field Cancerization Marker

Discovering DNA methylation changes in healthy tissue near colorectal polyps. [JNCI, 2024]

Survival Modeling with Knowledge Distillation

Fitting sparse survival models using deep model distillation. [Bioinformatics, 2024]

Multi-omics Model Robustness

Revealing the vulnerability of survival models to data noise. [Cell Reports Methods, 2023]

We offer Bachelor's and Master's student projects in machine learning, bioinformatics, and cancer research. See opportunities →