I study the architecture and dynamics of gene regulatory networks by integrating bulk, single-cell, and multi-omic data across biological systems, reconstructing how regulatory programs govern cellular fate, plasticity, and compensatory responses.
What I work on
- Gene regulatory network inference and benchmarking
- Single-cell, multi-omic, and bulk RNA-seq analysis across biological systems
- Network modeling of differentiation, stress response, and perturbation
- Scalable and reproducible computational workflows for regulatory genomics
What I bring
- Model-guided hypothesis generation and validation strategy support
- Experience translating network outputs into biologically actionable insights
- Comparative regulatory network analysis across differentiation, stress, and perturbation
Technical scope
- Data: bulk RNA-seq, scRNA-seq, multi-omic, time-course, and perturbation datasets
- Methods: network inference, trajectory inference, probabilistic graphical models
- Tooling: Python, R, Snakemake, Docker