Our research group focuses on developing computational approaches to analyze high-throughput drug and genetic screens, along with multi-omics datasets, to study the fundamental regulatory mechanisms underlying cancer cell response to treatments. Working closely with experimental and clinical groups, we develop integrative approaches to address one of the most pressing challenges in cancer: drug resistance.
We aim to develop the next generation of multidisciplinary engineers who can bridge the fields of computer science, cell biology, and biomedicine.
Machine Learning | Multi-omics | Functional Genomics | Drug resistance | Cancer
Postdoctoral Fellow at Wellcome Sanger Institute
Cancer Cells CRISPR-Cas9 Large-scale Screens
Prioritization of cancer therapeutic targets using CRISPR–Cas9 screens
We presented one of the largest CRISPR-Cas9 screens available to date, and developed a precision...
[Read More]
Crispy: CRISPR-Cas9 Copy Number Bias
Structural rearrangements generate cell-specific, gene-independent CRISPR-Cas9 loss of fitness effects
We developed a computational approach to correct copy-number driven deleterious bias induced by Cas9 double-strand...
[Read More]
Copy Number Buffering in Cancer
Widespread post-transcriptional attenuation of genomic copy-number variation in cancer
We built an efficient genome-wide association pipeline to test thousands of potential associations between genomics...
[Read More]
Oncometabolite Fumarate
Fumarate is an epigenetic modifier that elicits epithelial-to-mesenchymal transition
We showed that abnormal accumulation of fumarate leads to epigenetic alterations eliciting epithelial-to-mesenchymal transition (EMT)...
[Read More]