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Senoo Lab
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A lab that bridges biology and information science to analyze life science data.
AboutAbout the lab
Analyzing life science data with information science.
Senoo Lab tackles problems in biology and medicine, building on bioinformatics and information science.
The lab studies methods for analyzing a wide range of life science data, including single-cell omics, spatial omics, microscopy video images of cells, and biosignals such as EEG and ECG.
Although the subject matter is biology, the main research methods come from information science, and the lab's website says that limited knowledge of biology is not a problem.
Students can also take part in collaborative research with other fields, such as medicine, pharmacy, agriculture, and science.
Key terms
- Bioinformatics
- A field that analyzes life science data with methods from information science to draw out new findings
- Spatial transcriptomics
- A technology for examining which genes are active at which positions within a tissue. It analyzes spatial patterns of gene expression
- Cell community
- A unit this lab focuses on, positioned as a layer between cells and tissues
NewsLab news
A master's student won the Best Presentation Award at the 157th meeting of the IPSJ SIG on Mathematical Modeling and Problem Solving (MPS)
A master's student won the Best Presentation Award at the Mathematical Modeling and Problem Solving research presentation meeting
A research student won the Young Researcher Selected Poster Award at IIBMP2025 (Joint Conference on Informatics in Biology, Medicine and Pharmacology)
Senoo Lab was established
ResearchResearch themes
Senoo Lab develops data analysis methods that span measurement technologies such as single-cell omics, spatial omics, and live imaging, aiming for an integrated understanding of the life science hierarchy of molecules, cells, and tissues. In particular, it focuses on the "cell community," a layer between cells and tissues, and develops computational methods to reveal its structure and dynamics.
*Illustrative imageOmics Analysis
The lab develops computational science methods for analyzing large-scale gene expression data obtained with technologies such as next-generation sequencers. At the single-cell level, it examines cell states and differentiation processes; with spatial transcriptomics, it examines patterns of gene expression within tissues.
*Illustrative imageCell Video Image Processing
The lab develops image processing and machine learning techniques that automatically extract information on cell movement from microscope video images of cells. Its work includes observing the cell cycle with fluorescent probes and tracking cells with particle filters and deep learning.
*Illustrative imageBiosignal Processing and Medical Data Mining
The lab develops techniques to estimate internal human states, such as emotion, concentration, and comfort, from biosignals such as EEG, heartbeat, and electromyography (EMG). It also conducts research on extracting findings useful for predicting disease and evaluating treatment effects from electronic medical records and proteomics data.
MembersFaculty
The members of Senoo Lab consist of faculty, a visiting professor, project researchers, a secretary, and doctoral, master's, and undergraduate students.As of 2026
- ProfessorShigeto Senoo
- Associate ProfessorYuki Matsumoto
- Assistant ProfessorHironori Shigeta
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: “Fluidigm C1 Single-Cell Auto Prep system” Konrad Förstner / CC BY 2.0 (cropped)
- Omics Analysis: “Next generation sequencing slide” Bainscou / CC BY 3.0 (cropped)
- Cell Video Image Processing: “Fluorescence microscopy of the oral cancer cells” Korinna / CC BY 4.0 (cropped)
- Biosignal Processing and Medical Data Mining: “12 lead ECG” Peterhcharlton / CC BY 4.0 (cropped)
- Related lab (Kawahara Lab): “Artificial Neural Network with Chip” mikemacmarketing / original posted on flickr Liam Huang / clipped and posted on flickr / CC BY 2.0 (cropped)
- Related lab (Data Science Lab): “Antique one-armed bandit, Ventnor, Isle of Wight, UK” Ronald Saunders from Warrington, UK / CC BY-SA 4.0 (cropped)
- Related lab (Uranishi Lab): “ISS-50 Shane Kimbrough uses a virtual reality headset in the Destiny lab” NASA / Public domain (cropped)
- Related lab (Wakamiya Lab): “A starling murmuration at Eyemouth - geograph.org.uk - 6378647” Walter Baxter / CC BY-SA 2.0 (cropped)
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