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Kawaguchi Lab
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A bioinformatics lab that uses information science to decode the diverse states of cells.
AboutAbout the lab
How much of life is determined by information?
The Kawaguchi Lab uses computational life science and bioinformatics to understand biological phenomena common to all cells.
It is known that even among individuals or cells with the same genome, various differences (heterogeneity) arise.
Based on high-dimensional data, the lab seeks to clarify the mechanisms that determine various biological processes.
Using the latest information science and artificial intelligence technologies, the lab aims to understand biological systems in a form that humans can interpret.
Key terms
- Bioinformatics
- A field that analyzes biological data with computers to investigate the mechanisms of life
- Epigenome
- Information such as modifications attached to DNA. It determines which genes are active without changing the base sequence
- Deep learning
- A machine learning method that learns features from large amounts of data using neural networks with many stacked layers
ResearchResearch themes
It has become possible to measure vast amounts of data at once, bringing the true nature of cells within reach. However, discovering the mechanisms needed to make sense of such data is still a work in progress. The lab uses high-dimensional data to uncover the mechanisms that determine biological processes.
*Illustrative imageSingle-Cell Epigenomics
The lab analyzes data from technologies that measure the epigenome, which consists of modifications on DNA, one cell at a time. Focusing on "epigenetic memory," in which cells retain the state they were in before reprogramming, the lab aims to predict and understand gene regulatory networks through meta-integrative analysis and deep learning.
*Illustrative imageMachine Learning with Small, Heterogeneous Data and Healthcare DX
In medicine, diverse information such as patients' backgrounds, genetic mutations, and images must be handled at the same time. The lab properly harmonizes medical data, builds the foundation for applying machine learning, and tests whether results remain stable across hospitals.
MembersFaculty
The members of the Kawaguchi Lab consist of faculty, assistants, doctoral and master's students, and undergraduates.As of 2026
- Associate ProfessorRisa K KawaguchiPublications ↗
VoicesStudent voices
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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: “Normalized Linkage Heat Map” CP2000A / CC BY-SA 4.0 (cropped)
- Single-Cell Epigenomics: “Epigenetic mechanisms” National Institutes of Health / Public domain (cropped)
- Machine Learning with Small, Heterogeneous Data and Healthcare DX: “Electronic Health Records flow chart” uploaded by Library 046 at en.wikipedia / Public domain (cropped)
- Related lab (Molecular Biology Lab): “Neural Stem Cells” Welcome Collection / CC BY-SA 4.0 (cropped)
- Related lab (Physiological Chemistry Lab): “Mitotic LLC-PK1 cells, fluorescence microscopy ( )” ZEISS Microscopy from Germany / CC BY 2.0 (cropped)
- Related lab (Genetics Lab): “Drosophila melanogaster under microscope” Talita Oliveira / CC BY-SA 4.0 (cropped)
- Related lab (Ota Lab): “Flow Cytometer (NIH BioArt 160)” Courtesy of NIAID Ryan Kissinger / Public domain (cropped)
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