LAB LOGA page on LabLog, a review site (not the lab's official page)
Tsunoda Lab
Machine-translated · View original
A lab that uses deep learning and quantum computing to uncover the relationship between cancer and immunity.
AboutAbout the lab
Unraveling disease and biological phenomena through advanced mathematical science.
The Tsunoda Lab aims to overcome diseases such as cancer by studying how diseases are related to biological phenomena such as immunity.
The lab analyzes huge volumes of biomolecular data obtained from many clinical specimens using methods such as deep learning and quantum computing.
The lab finds new causes of disease, reconstructs the relationships among those causes as a network, and thereby understands the mechanisms of disease as a whole.
The lab places more emphasis on analytical methodology than on experiments, and attracts a diverse mix of people, including clinicians, researchers who love mathematics, and international researchers.
Key terms
- Tumor microenvironment
- The environment surrounding cancer cells, including immune cells and stromal cells, which influences how the cancer behaves.
- Omics
- Data that comprehensively measure biological molecules as a whole, such as the genome and gene activity.
- Single-cell RNA-seq
- A method for measuring which genes are active, and how active they are, in each individual cell.
NewsLab news
A paper by a doctoral student has been published
A paper by a doctoral student has been published
A master's student received the Dean's Award of the Graduate School of Frontier Sciences
A review article on AI and machine learning for predictive medicine was published in the Journal of Human Genetics
A master's student received the ERA Award (the top master's award) of the Department of Computational Biology and Medical Sciences
ResearchResearch themes
Aiming to overcome diseases such as cancer, the lab analyzes big data obtained from clinical specimens, including omics, images, and clinical information, using new methods based on deep learning and quantum computing. It quantitatively reconstructs the relationship between cancer cells and their microenvironment, with the goal of predicting treatment response and side effects for each patient.
*Illustrative imageThe relationship between cancer and its microenvironment
The lab unravels the relationship between populations of cancer cells and their microenvironment, including immune cells, and predicts treatment response and the acquisition of resistance for each patient. In joint research with Keio University School of Medicine, it showed that cancer cell populations that differ from location to location create an environment that suppresses immunity.
*Illustrative imageMethodology for analysis with deep learning
The lab devised the DeepInsight method, which converts omics data into image-like form so that it can be analyzed with deep learning. It also proposed a method for examining what a deep learning model looks at when it makes a classification, and used it to discover a new signaling pathway that reflects the individual characteristics of cancers.
*Illustrative imagePredicting response to anticancer drugs
Extending the DeepInsight method, the lab proposed an approach that predicts each patient's response to anticancer drugs from multiple types of omics data. It also found gene patterns linked to differences in drug response.
*Illustrative imageIdentifying cell types from single-cell data
The lab proposed a deep learning method that converts single-cell RNA-seq data into images with the DeepInsight method and identifies cell types and their finer subtypes with high accuracy, taking the hierarchy of the classification into account.
MembersFaculty
The members of the Tsunoda Lab consist of faculty, postdoctoral researchers, doctoral and master's students, secretaries, and visiting collaborative researchers.As of 2026
- ProfessorTatsuhiko Tsunoda
- Associate ProfessorArtem Lysenko
VoicesStudent voices
Ratings and reviews reflect the experiences of individual current or former students, not the lab's official views. Whether a lab has reviews, or how many, says nothing about the lab itself.
Students who take part in an interview may receive a thank-you gift worth ¥1,000, regardless of what they say.
Student ratings (0 students)
--
--
--
--
--
--
Student voices answer questions like these
- What's great about this lab?
- What did you learn after joining?
- What's the vibe, and what is the professor like?
- Who is this lab for?
- Where do graduates go?
Your experience can help younger students choose their lab. Your name won't be shown.
Write a lab reviewAnonymous · Your draft is saved if you stopRelatedLabs similar to Tsunoda Lab
Suzuki LabFaculty of Science, Department of Bioinformatics and Systems BiologySystem-level elucidation of how human genome variants give r…
Toyoshima LabFaculty of Science, Department of Bioinformatics and Systems BiologyElucidation of information-processing mechanisms of neural c…
Kuroda LabFaculty of Science, Department of Bioinformatics and Systems BiologyDynamic mechanisms of intracellular signal transduction, ana…
Frith LabFaculty of Science, Department of Bioinformatics and Systems BiologyDeciphering the function and history of gene sequences using…The information on this page is compiled by the LabLog team from the lab's public information and interviews. For corrections or removal requests, please contact LabLog, not the lab.
Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “IBM Quantum System One” OJB Quantum / CC BY 4.0 (cropped)
- The relationship between cancer and its microenvironment: “Killer T cells surround a cancer cell” The National Institutes of Health / Public domain (cropped)
- Methodology for analysis with deep learning: “Convolutional neural network, maxpooling” Daniel Voigt Godoy / CC BY 4.0 (cropped)
- Predicting response to anticancer drugs: “Taxol(Paclitaxel)3D” Itineranttrader / Public domain (cropped)
- Identifying cell types from single-cell data: “Red White Blood cells” Electron Microscopy Facility at The National Cancer Institute at Frederick (NCI-Frederick) / Public domain (cropped)
- Related lab (Suzuki Lab): “Illumina HiSeq 2500” Konrad Förstner / CC0 (cropped)
- Related lab (Toyoshima Lab): “Adult Caenorhabditis elegans” Zeynep F. Altun, wormatlas.org / CC BY-SA 2.5 (cropped)
- Related lab (Kuroda Lab): “Insulin Structure” Webridge / CC BY-SA 3.0 (cropped)
- Related lab (Frith Lab): “DNA double helix 45” Jerome Walker,Dennis Myts / Public domain (cropped)
About LabLog
LabLog is a lab review app for students only. Student members at each university interview students in labs and publish what they say. Student voices can only be read by students who sign up with a university email address. Operated by bestiee Inc.
Learn more about LabLog ↗Search engines and AI may reference the basic lab info and rating summaries on this page and the description of LabLog. Student voices are for student members only. Automated collection by programs (scraping, or input to or training of AI) is prohibited under Article 8 of the Terms of Service. If you need data for research or analysis, please contact us.