Research Projects

Rice landraces are diverse traditional rice varieties passed down from generation to generation by farmers. These varieties have unique genetic characteristics that have not yet been thoroughly studied or used to improve modern rice crops. The research project aims to combine genomic data with machine learning methods to study the genetic diversity of rice landraces and how it can be used to improve modern rice varieties. The study will use in-house genomic data from a previous project and data from the International Rice Research Institute (IRRI) to analyze large datasets. We will apply deep learning tools and machine learning methods to compare the genomes of rice landraces with improved rice varieties. By doing this, we hope to identify novel genetic variations that are associated with important traits such as yield, stress tolerance, and nutritional quality. This study will be the first of its kind to use machine learning methods to analyze the genomes of rice landraces, and it is expected to provide new insights into the use of germplasm in other crops. Collaborating with computer science experts will allow the researchers to utilize the most advanced machine learning methods to analyze the large amounts of genomic data generated from the project. The collaboration will also provide new perspectives on genomic features and contribute to training a new generation of students and scholars in this field.