projects

Development of image processing methods to quantitatively analyze cellular dynamics
We develop a computer-assisted analysis method based on image processing and machine learning to study developmental dynamics at single cell resolution.

Computational analysis of nuclear division dynamics extracted from 4D DIC microscopy images
Bioimage informatics techniques can quantify nuclear division dynamics of RNAi-treated embryos from over 1000 sets of 4D DIC microscopy images. Our collection provides novel opportunities to develop computational methods for understanding animal development.

Data-driving approach by focusing on microscopy images stored in public databases
By developing image processing systems, we provide over 1,500 sets of nuclear division dynamics data extracted from C. elegans RNAi embryo’s movies in Phenobank. The datasets can be used to obtain new quantitative knowledge about genotype-phenotype relationships in early embryogenesis.

Mechanical environments for embryonic development
Mechanical interactions between cell-cell and cell-extracellular matrix play a key part in differentiation and morphogenesis for embryonic development. We are studying how mechanical environments around an embryo affect developmental processes using C. elegans.

Physical bioinformatics of the dynamic 3D genome organization
Our theoretical and computational methods allow for bridging the gap among the 3D genome information by high-throughput chromosome conformation capture (Hi-C), genome dynamics information by live-cell imaging and epigenome information on chromatin.

SSBD database (Systems Science of Biological Dynamics database)
SSBD is an open public database for storing and sharing microscopy image data and quantitative data of biological dynamics, allowing biologists and researchers to reuse their data and findings. It was part of the life science database integration project in Japan led by National Bioscience Database Center (NBDC) and Japan Science Technology Agency (JST).

Integrated data platform for life science project
We provide peta-bytes scale storages and computation environments for life science image data and quantitative data to share the data for analysis, collaboration, and data archive.