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Bioinformatics Lab
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The lab analyzes large-scale life science data to tackle problems in medicine and biology.
AboutAbout the lab
Looking into data and pioneering new technologies
The Bioinformatics Lab studies bioinformatics, which solves problems in medicine and biology through computers and large-scale data.
Bioinformatics is the field that processes and analyzes large-scale life science data so that people can understand and interpret the behavior of living systems hidden in the data.
The lab's website describes bioinformatics as something like a microscope or telescope for looking into data.
The lab works both on developing technologies and on applied and collaborative research.
Key terms
- Bioinformatics
- The field that processes and analyzes large-scale life science data so that the behavior of living systems hidden in the data can be understood
- Single-cell
- An approach that measures cells one at a time. It yields high-dimensional data, from hundreds to tens of thousands of dimensions per cell
- Transcription factor
- A protein that recognizes and binds specific sequences in the genome and regulates the activity of target genes
- ChIP-seq
- A method that comprehensively measures, across the whole genome, the sites where transcription factors bind
NewsLab news
A paper with a graduate student as co-first author was published in microPublication Biology
A researcher's practical guide to single-cell RNA-seq analysis was published in Neuroscience Research
A master's student received the Outstanding Presentation Award of the Frontier Medical Sciences Degree Program
ResearchResearch themes
The lab develops new bioinformatics technologies, aiming to draw out, from large-scale life science data, an understanding and interpretation of the mechanisms, diseases, and abnormalities of various organisms, including humans. Ongoing themes include automating biological research, decoding single-cell and spatial transcriptomes, and applying machine learning.
*Illustrative imageAnalysis and visualization of single-cell data
The lab develops technologies to visualize and analyze the high-dimensional data obtained from single-cell measurements. Examples include Millefy, which lets researchers view many cells at a glance (joint research with RIKEN), and CCPLS, which estimates how the types of surrounding cells affect gene expression.
*Illustrative imageResearch toward laboratory automation
In joint research with RIKEN, the lab develops SLab, a scheduling method that decides when and in what order to operate equipment such as laboratory robots. The lab built, together with another lab at the university, a system that automates yeast growth assay experiments using a liquid-handling robot.
*Illustrative imageDiversity of sequences recognized by transcription factors
The lab investigates the sequences recognized by transcription factors using MOCCS, a method that extracts them from ChIP-seq data. By analyzing large-scale human data, the lab explores how the recognized sequences vary across transcription factors and cell types.
MembersFaculty
The members of the Bioinformatics Lab are faculty, researchers, administrative staff, doctoral and master's students, and research assistants.As of 2026
- Associate ProfessorHaruka Ozaki
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: “Eppendorf epMotion 5075 liquid handling robot” Magnus Manske / CC BY-SA 3.0 (cropped)
- Analysis and visualization of single-cell data: “Flow Cytometer (NIH BioArt 160)” Courtesy of NIAID Ryan Kissinger / Public domain (cropped)
- Research toward laboratory automation: “Biomek NXP lab robot” real name: Nadina Wiórkiewicz pl.wiki: Nadine90 commons: Nadine90 / CC BY-SA 3.0 (cropped)
- Diversity of sequences recognized by transcription factors: “TATA-box-binding protein within the Crystal Structure of the NC2-TBP-DNA Ternary Complex 1JFI” Kamada, K., Shu, F., Chen, H., Malik, S., Stelzer, G., Roeder, R.G., Meisterernst, M., Burley, S.K., New York SGX Research Center for Structural Genomics (NYSGXRC) / CC0 (cropped)
- Related lab (Life Systems Science Lab): “Laptop coding programs (Unsplash)” Tirza van Dijk tirzavandijk / CC0 (cropped)
- Related lab (Digital Behavioral Science Lab (WPI-IIIS)): “Single person cabin in the night train from Budapest to Berlin” Alex Sirac / CC BY 4.0 (cropped)
- Related lab (Medical Mathematical Informatics Lab): “Laptop and stethoscope ( )” jfcherry / CC BY-SA 2.0 (cropped)
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