Bhardwaj Lab

Quantitative Biology and Data Integration

Institute of Biodynamics and Biocomplexity, Utrecht University

Our mission

Our lab’s ultimate goal is to transform human medicine by learning how to program stem cells directly inside the body. If we can guide these master cells to become specific, functional cell types, we can unlock powerful new therapies for regenerative medicine, healthy aging, and cancer.

To achieve this, we study how cells make 'fate decisions'. Even though every cell in our body shares the same DNA code, they develop unique identities during embryonic development. They do this by modifying their epigenetic landscape—a molecular scaffolding that determines which genes are turned on or off. This process is tightly controlled by regulatory proteins called 'transcription factors' working within the cell's 'chromatin' environment (the structural way DNA is packaged).

By mapping the precise, dose-response relationships between these epigenetic factors and cellular choices, we can learn how to efficiently rewrite a cell's identity.

Learn more about epigenetic reprogramming →

Our approach

In recent years, technology has been developed to systematically map the chromatin landscape of individual cells, and quantify the levels of transcription factors. This allows us to build data-driven models that explain the role of these key players in cellular decision-making.

In our research group, we apply such technology (specifically, single-cell and single-molecule genomics methods) to understand cellular decision-making. These experiments generate massive, complex datasets, typically measuring thousands of genes within thousands (and sometimes millions) of individual cells or molecules. We use this data to build statistical and machine learning models that can uncover the relationship between these regulators and a the cell's current or future state.

Learn more about our technologies →

Our Projects

We take a data-driven approach to biology, splitting our focus between two major pillars:

Discovery: understanding cellular decision-making by extracting new insights from epigenomics and multi-omics data.

Engineering: building new bioinformatic methods and tools to analyse the data from such emerging technologies, and making them accessible to biologists.

Learn more about our projects →