Research
Towards a systems understanding of plant responses to signals
We are interested in understanding how plants, as sessile organisms, sense, integrate and respond to the environmental and developmental signals for optimal growth. Our unique interests are:
- The diversity of regulatory mechanisms of gene expression, including but not limited to chromatin modifications, transcription factors, and RNA processing.
- How genes function as networks
- How to best combine statistics and programming with excellent molecular work to derive biological insights
We currently focus on the following research topics:
1) Understanding the chromatin regulations of specialized metabolism
The goal is to identify chromatin regulatory mechanisms that coordinate the specialized metabolic networks, so that plants can produce the right products at the right place and right time for the right audience! This includes developing our understanding of how histone acetylation contributes to coordinating the floral volatile metabolites pathways, or how DNA methylation mediates the flavoring compounds in grape berries.
2) Gene regulatory network of plant nutrient use
Chemical fertilizer is a blessing but also a curse. How can we best supply nutrients to our plants without damaging our environment? Within this broad goal, we ask if big data approaches could help to elucidate the complex gene regulatory network of plant nitrogen metabolism, with a focus on chromatin regulatory mechanisms.
3) Application of ML and AI in functional genomics
The past few years have seen rapid advancements in machine learning and artificial intelligence, driven particularly by deep neural networks. We are at the forefront of integrating cutting-edge deep neural network tools, including natural language processing algorithms, with the vast wealth of functional genomics datasets. Our goal is to decode the regulatory information in plant genomes that would otherwise remain elusive.