Category: SSBD

[Press Release] Development of life sciences by sharing image data

Drs Koji Kyoda, Hitoya Itoga, Yuki Yamagata (RIKEN R-IH), et al. developed and published a public repository and high-value database that facilitates the sharing and re-using of image data in the life sciences. In this paper, we describe the international positioning and functions of the SSBD.

The SSBD is positioned as one of the core ecosystems of the international consortium ‘foundingGIDE’, which aims to promote the standardisation and sharing of FAIR image data, and is expected to enhance the transparency and reliability of science and contribute to the development of science throughout society through the advancement of open science. The project is expected to contribute to the development of science in society as a whole through the advancement of open science.

Learn more about the study on Press Release by RIKEN. (In Japanese only)

Reference

Kyoda, K., Itoga, H., Yamagata, Y., Fujisawa, E., Wang, F., Miranda-Miranda, M., Yamamoto, H., Nakano, Y., Tohsato, Y., Onami, S.(2024) SSBD: an ecosystem for enhanced sharing and reuse of bioimaging data. Nucleic Acids Res. gkae860. https://doi.org/10.1093/nar/gkae860

[Press Release] Development and publication of the zebrafish brain gene expression database

Dr Towako Hiraki-Kajiyama(Assistant professor at Graduate School of Life Science, Tohoku University, former researcher at RIKEN CBS) and Yoshihiro Yoshihara (TL at Riken CBS) et al. with Drs Hiroya Itoga and Shuichi Onami established the database for scanned data of brain sections of zebrafish.

The database uses SSBD (https://ssbd.riken.jp/) and OMERO (https://openmicroscopy.org) as infrastructures.The database and anatomical findings will contribute to future neuroscience research using zebrafish.

Learn more about the study on Press Release from RIKEN. (In Japanese only)

Reference

Hiraki-Kajiyama, T., Miyasaka, N., Ando, R., Wakisaka, N., Itoga, H., Onami, H. I. S., & Yoshihara, Y. (2024). An atlas and database of neuropeptide gene expression in the adult zebrafish forebrain. Journal of Comparative Neurology, 532, e25619. https://doi.org/10.1002/cne.25619

SSBD in Experimental Medicine.

A contribution by Drs Kyoda and Onami on the current status and prospects on bioimaging database has been published in a magazine, Experimental Medicine.

AJACS12 Registration is Open

Our team leader Dr Shuichi Onami is giving a lecture titled “BioImaging database” at the AJACS online 12 on August 25, hosted by JST-NBDC.

This workshop is aimed to educate how to use databases and tools in life sciences as well as introduce activities for databases integration.

AJACS online 12

  • Date and Time: August 25, 2022 13:30~15:50
  • Venue: Online
    • Meeting URL will be announced to participants.
  • Fees: Free
  • Host:  Japan Science and Technology Agency (JST)
  • Registration required at the workshop website.

For more details, please go to the AJCS online 12 website (in Japanese only):

パスウェイ＆画像データベースを知って・学んで・使う（AJACSオンライン12）

We look forward you to joining the workshop!

[Press Release] Launch of “NeuroGT Database”, a brain atlas of neurogenic tagging CreER mouse drivers

Drs. Yukako Tohsato and Hiroya Itoga in our SSBD team, together with Prof. Tatsumi Hirata (NIG) and colleagues, developed the “NeuroGT database,” which contains whole-brain image data of tagged neurons based on time of neurogenesis. Through NeuroGT, researchers can find suitable neurogenic tagging driver lines for their research.

Learn more about Neuro GT on the National Institute of Genetics Press Release.

Reference

Hirata, T., Tohsato, Y., Itoga, H. et al. NeuroGT: A brain atlas of neurogenic tagging CreER drivers for birthdate-based classification and manipulation of mouse neurons. Cell Rep. Methods 1, 100012 (2021). https://doi.org/10.1016/j.crmeth.2021.100012

RIKEN Hackathon FY2019 – TIFF image ROI contours written to BDML/BD5 format using Galaxy workflow

SSBD team attended the RIKEN Hackathon FY2019 and developed a software tool in Python that allows the ROI contours of a TIFF image to be saved into BDML/BD5 format using Galaxy workflow. The tool can be used separately from Galaxy.

https://github.com/openssbd/python-bdml

* BDML/BD5 is an open format based on XML and HDF5 for representing quantitative biological data with spatiotemporal dynamical information. ref: Kyoda K, et al. (2015) Bioinformatics, 31(7): 1044-52. https://doi.org/10.1093/bioinformatics/btu767