Shimizu lab addresses evolutionary and ecological questions in integrated biological sciences by exploiting novel genomics tools and machine learning. The research themes include robustness of polyploid species, language evolution, evolution of mating systems, and gene expression and image analysis in naturally fluctuating conditions termed in natura.

 

Plant phenotyping plays a key role in the understanding of plant responses to seasonal environmental fluctuations. To this end, the lab has established the plant phenotyping method PlantServation with one unit of the hardware part (i.e., image acquisition platform) consisting of four cameras capturing approximately eight square meters. The acquired images are processed by the software part (i.e., image analysis pipeline) using machine learning. So far, PlantServation has been deployed for monitoring Arabidopsis relatives and wheat. Upon interest the experience and know-how accumulated in the lab could be shared for further application.