In our laboratory, we are conducting research by applying machine learning to biotechnology. In this research, biological functions are estimated and distinguished from gene sequence information by deep learning and statistical methods. Specifically, machine learning input data is collected through biological experiments using the latest equipment such as next-generation sequencers and cell sorters. This idea is expected to develop in a wide range of fields such as agriculture, engineering and medicine. Machine learning is being studied all over the world, but there are very few laboratories that do not have a boundary between wet and dry. By applying machine learning to biological experiments, we aim at more efficient substance production and strict gene expression control in E. coli.
