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Health Medical Intelligence Lab
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The lab uses big health and medical data such as genomes and health checkups to predict and prevent disease.
AboutAbout the lab
From health and medical data to disease prevention
The Health Medical Intelligence Lab studies how to use diverse health and medical data to predict and prevent disease and to maintain health.
The lab works with human genomes, multi-omics data, health checkup and insurance claims data, and metagenomic data of the bacterial and viral communities that live in symbiosis with humans.
Based on Bayesian statistics, machine learning, and deep learning, the lab develops theory and methodology for analyzing big data.
Analyses are run on SHIROKANE, the supercomputer at the Human Genome Center.
Associate Professor Kotoe Katayama and colleagues also study algorithms for solving biological, medical, and chemical problems by computer, as well as databases of chemical reaction systems of biomolecules.
Key terms
- Multi-omics data
- Data that comprehensively measure the molecules in the body across many layers, such as the genome, gene activity, and proteins
- Metagenome
- A method, and the resulting data, for reading and analyzing together the genomes of the many microbes living in places such as the gut
- Algorithm
- The procedures and rules of calculation used to make a computer solve a problem
NewsLab news
Contributed "The Frontier of Commensal Virus Genome Analysis" to a special feature on gut virome analysis in Jikken Igaku (Experimental Medicine)
A paper by a doctoral student was published in Bioinformatics Advances
Published in Communications Biology on the relationship between genetic clusters revealed by genome analysis and lifestyle behaviors
A paper on metagenotype analysis software was published in NAR Genomics and Bioinformatics
Elucidated how enterococci involved in severe acute graft-versus-host disease evade antibiotics
ResearchResearch themes
The lab studies how to use diverse health and medical data to predict and prevent disease and to maintain health, and aims to create intelligence that can be put into practice in society. Its work covers analysis of genome, health checkup, and symbiotic microbe data, as well as algorithms for the life sciences.
*Illustrative imageHuman genome data analysis technologies
The lab develops methods to analyze new kinds of data produced by cutting-edge measurement technologies such as long-read and single-cell sequencing. It also uses AI to interpret clinically the mutations found in whole-genome data from cancer, with the aim of leading to new genomic medicine.
*Illustrative imageHealth checkup data analysis technologies
The lab develops technologies that analyze health checkup data together with time-series data on individuals' lifestyle habits, in order to predict health status and simulate disease risk. In collaboration with Hirosaki University COI-NEXT, it also works on delivering concrete action plans for health promotion.
*Illustrative imageGenome data analysis of symbiotic microbes
The lab develops methods to analyze metagenomic data of the bacterial and viral communities that live in symbiosis with humans. It works on elucidating the mechanisms of diseases caused by disruption of the bacterial community, and on developing AI that finds phages capable of killing the causative bacteria.
*Illustrative imageAlgorithms and databases for the life sciences
The lab designs and analyzes algorithms for solving biological, medical, and chemical problems by computer, and builds an integrated database of chemical reaction systems of biomolecules.
MembersFaculty
The members of the Health Medical Intelligence Lab consist of faculty, technical staff, project researchers, academic specialist staff, administrative staff, visiting researchers, doctoral students, non-degree research students, research trainees, and research students.As of 2025
- ProfessorSeiya ImotoPublications ↗
- Associate ProfessorYaozhong Zhang
- Associate ProfessorKotoe Katayama
- Assistant ProfessorNoriaki SatoPublications ↗
- Project Assistant ProfessorSatoshi Ito
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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: “Sky spectral karyotype” Courtesy: National Human Genome Research Institute / Public domain (cropped)
- Human genome data analysis technologies: “Sanger sequencing read display” Loris / Public domain (cropped)
- Health checkup data analysis technologies: “Blood collection renal function test tube” Fumikas Sagisavas / CC0 (cropped)
- Genome data analysis of symbiotic microbes: “Enterobacteria phage T2 transmission electron micrograph” SnaxMikn / CC BY-SA 4.0 (cropped)
- Algorithms and databases for the life sciences: “Anaheim Stadium on opening day” Los Angeles Times / CC BY 4.0 (cropped)
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