The 6th RIKEN-KI-SciLifeLab Symposium: Biomedical Data for Artificial Intelligence

November 6-7, 2019


[Date] November 6-7, 2019

RIKEN Yokohama Campus

Please register from HERE. For the details of the agenda, please read [Agenda]

[Symposium aims]
The 2019 symposium at RIKEN Yokohama will address two points
• Produce a White Paper detailing the biomedical/life science areas for which RIKEN, Karolinska Institute and SciLifeLab see large potential for AI contributions to life sciences
• Generate biomedical/life science reference datasets to attract AI researchers and open these datasets at the RIKEN and SciLifeLab Data Centers

"Artificial Intelligence Meets Life Sciences" was the 2018 symposium topic in this symposium series where we surveyed ongoing AI activities related to Biomedical/Life Sciences at RIKEN and KI/SciLifeLab. An intense discussion on the second day was summarized in an "Opinion Report" with two main conclusions:
a) The scientific community should produce life sciences reference datasets in strategic areas for AI applications to attract AI researchers.
b) Life science areas should be identified which would strongly benefit from AI.

A tangible deliverable for this year's symposium is a White Paper addressing b) above. Contents will be co-created at the symposium, edited immediately thereafter, and structured into a quality-controlled finished paper. Symposium participants will be invited to refine the co-created output as co-authors under the supervision of one Swedish and one Japanese co-editor. The White Paper will serve to document the opportunities and challenges right now, so that a current cross-cultural and cross-discipline perspective is provided. Since there is not a particular stakeholder group for which the White Paper is written, publishers will be contacted for wide dissemination. Peer reviewing will then further improve quality and readability. The ambition is to attract readership from both the AI side and the biomedical/life sciences side with applied/clinical as well as basic research interests.

[Symposium history]
This symposium series is organized between RIKEN in Japan, and the Karolinska Institute and the Science for Life Laboratory (SciLifeLab) in Sweden. The symposia alternate between RIKEN and SciLifeLab. The 2019 symposium will be the sixth one and will be held at RIKEN in Yokohama.
The overall main goals of the symposia are to a) identify common scientific interests between RIKEN and SciLifeLab, b) identify complementary skills and technologies for collaborations and c) encourage the exchange of Ph.D. students and postdocs between RIKEN and SciLifeLab/KI. Several collaborations between groups at KI, SciLifeLab and RIKEN started based on first contact during one of the symposia.

Each symposium is centered on one specific topic. Topics from previous years were: Molecular Imaging and Genomics (2014), Structural Biology for Drug Discovery (2015), Decoding Health and Disease with a) Imaging & Disease, b) RNA & Disease, c) Single, Rare and Stem cells & Disease (2016), Life Science Frontiers in Health, Disease and Aging, with sessions a) Gene Expression in Disease and Aging, b) Neural Function, Disease and Therapy, c) Molecular Aspects of Health, Disease and Aging, d) Visualizing Health, Disease and Aging, e) Molecular Network Control (2017).


[List of speakers from Japan and Sweden]

  • Erik Aurell (KTH Royal Institute of Technology, Sweden)
  • Magnus Boman (KTH Royal Institute of Technology, Sweden)
  • Mikael Huss (Karolinska Institutet, Sweden)
  • Eiryo Kawakami (RIKEN MIH)
  • Masaru Koido (RIKEN IMS)
  • Andreas Lennartsson (Karolinska Institutet, Sweden)
  • Yasuhiro Murakawa (RIKEN IMS-IFOM)
  • Shuichi Onami (RIKEN BDR, RIKEN Data Center)
  • Nicholas Parrish (RIKEN IMS)
  • Johan Rung (Uppsala University, Sweden)
  • Kazuhiro Sakurada (RIKEN MIH)
  • Kei-ichiro Suzuki (RIKEN IMS)
  • Ichiro Taniuchi (RIKEN IMS)
  • Sumithra Velupillai (King's College London, UK)
  • Yibo Wu (RIKEN IMS)
  • Hideyuki Yoshida (RIKEN IMS)
  • Katsuyuki Yugi (RIKEN IMS)
  • Aleksej Zelezniak (Chalmers University of Technology, Sweden)



Presentations from both AI and Life Sciences researchers will be given on Day 1. The speakers will focus on the (potential) applications of AI methods to Life Science data including ongoing work but also providing their views on near future application of AI methods for Life Sciences.

Day 2 of the symposium will be conducted as a workshop with active contribution from the participants and will be dedicated to the following two aims:

The first aim, which will be addressed in the morning session, is todiscuss and collect suggestions around challenges in Life Sciences for which we see as suitable applications for Artificial Intelligence
methods. During the discussion, all participants are invited to co-create the first version of a White Paper. A core group of authors will continue working on the White Paper with the goal to publish in an international peer-reviewed journal in 2020.

The second aim, which will be addressed in the morning and afternoon sessions, is to establish a roadmap for the creation of "AI-ready Life Sciences reference datasets". We will first discuss the requirements of the AI community for Life Sciences datasets. We will then break out into smaller groups consisting of both AI experts and Life Sciences experts. These groups will start the concrete planning for establishing reference datasets for different strategic areas such as genomics, transcriptomics, proteomics, epigenomics, population genetics, and the gut microbiome. Most likely, the descriptions of already published datasets will be improved to reach the "AI-ready level". Reference datasets will be made available through the RIKEN and SciLifeLab Data Centers within 2020.

The 6th RIKEN-KI-SciLifeLab Symposium: Biomedical Data for Artificial Intelligence AGENDA (PDF), Abstract (PDF)

[Symposium Co-Organizers]

  • Erik Arner (RIKEN IMS)
  • Magnus Boman (KTH Royal Institute of Technology, Sweden)
  • Carsten Daub (RIKEN IMS)
  • Takaharu Okada (RIKEN IMS)
  • Todd Taylor (RIKEN IMS)
  • Piero Carninci (RIKEN IMS)
  • Tadashi Yamamoto (RIKEN IMS)