Dr Onami in Experimental Medicine.

A contribution by Dr Onami, “Development of data format standards and data sharing systems for bioimaging” has been published in a magazine, Experimental Medicine.

Texture-Based Screening to Identify Genes Involved in Reproductive Aging in C. elegans

Dr Momoko Imakubo et al.’s study on analysis of genes involved in reproductive aging in C. elegans oocytes by using an image database of RNAi embryos and image processing has been published online at https://doi.org/10.17706/ijbbb.2021.11.3.40-49.

Congratulations to our former student trainee Momoko Imakubo who earned her PhD from Kobe University in March 2021 on her achievement. We wish you all the best in your future endeavour!

New Paper by Momoko Imakubo

A new paper by Momoko Imakubo, Student Trainee in the Onami lab, was published in the BMC Bioinformatics.

In this paper, we quantified age-associated changes in oocyte appearance in the nematode Caenorhabditis elegans by statistical image processing. We showed that the oocyte cytoplasmic texture in Nomarski differential interference contrast images significantly changes with aging.


Paper Published by Dr. Yamagata

Dr. Yuki Yamagata, Research Scientist in the Onami lab, co-authored a review paper with Dr. Hiroshi Masuya, RIKEN BRC, et al. The paper was published in the January issue of Laboratory Animal Research.

The RIKEN BioResource Research Center released an integrated database of bioresources including, experimental mouse strains, Arabidopsis thaliana as a laboratory plant, cell lines, microorganisms, and genetic materials using Resource Description Framework-related technologies in 2020. This review summarizes the features of current version of databases related to mouse strain resources in RIKEN BioResource Research Center and discusses future views. 


TL’s talk in Symposium went public

Team Leader Dr. Onami attended an online open symposium “
Prospects for next-generation integrated bioimaging and mathematical collaboration” which was organized by the Science Council of Japan in October. His presentation is now available online.

This symposium was aimed to discuss a theme: ” Will the advanced fusion of imaging technology and mathematical/ information science lead to a paradigm shift in life science? ” in Japan with not only researchers in the field of advanced bioimaging measurement but also researchers in a wide range of fields such as mathematics, physics, and information science.

To watch his talk visit our multimedia page.

Other presentations and discussions are available on the symposium website. The website and all videos were only in Japanese.

Watch TL’s Talk in GBI EoE V.

Our Team Leader Dr. Onami joined an international virtual workshop on “Pre-publication image management and processing” by the Global BioImaging, The Exchange of Experience Ⅴ (EoE V), in September.

His presentations as well as other experts’ in the bio-imaging data sharing field and discussions are available to watch online at the EoE V website.

Or visit our multimedia page.

Dr. Shinkai in SANKEI SHINBUN.

Dr. Soya Shinkai wrote his essay in a series of articles by RIKEN in THE SANKEI SHINBUN .

To read the article, visit the SANKEI NEWS website (in Japanese only).

New Paper by Koji Kyoda

We are pleased to announce that a new paper by Koji Kyoda, a Research Scientist in Onami lab, et al. was published in PLOS ONE.

In this paper, we developed the BD5, a new binary data format based on HDF5. It can be used to represent quantitative data of biological dynamics obtained from bioimage informatics techniques and mechanobiological simulations. BD5 allows fast access to quantitative data and fast transfer of files containing large quantitative data.

doi: 10.1371/journal.pone.0237468

Read Our Latest Press Release

A press release introducing the PHi-C, an original simulation method of the Hi-C data analysis by Dr. Soya Shinkai, has been issued.

We have discovered a formula that links the contact probability in Hi-C matrix data and the interaction parameter of the polymer network model. Using Hi-C matrix data as input, the PHi-C method allows for the simulation of the dynamic 3D genome in living cells.

Read the full press release article regarding PHi-C in Japanese on RIKEN website.


Soya Shinkai, et al. (2020) PHi-C: deciphering Hi-C data into polymer dynamics. NAR Genom. Bioinform. doi: 10.1093/nargab/lqaa020