Rice Landraces Genome Exploration

Project Objectives & Methods

Our research combines advanced genomics with machine learning to:

Analyze genetic diversity in rice landraces using genomic data (in-house & IRRI).
Apply deep learning and ML to compare landrace and improved variety genomes.
Identify novel genetic variations linked to yield, stress tolerance, and nutritional quality.
Provide insights for germplasm utilization in rice and other crops.
Foster collaboration between genomics and computer science experts.

Utilizing large datasets from CUK and IRRI repositories.

Applying cutting-edge ML/DL tools for genomic comparison and feature discovery.

Focusing on identifying genes for improved agricultural traits.

Explore our work and discover the future of rice improvement through data-driven genomics.