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Biometry Lab
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A lab of statistics and algorithms that draws knowledge from vast amounts of biological data.
AboutAbout the lab
Let's draw knowledge from information.
The Biometrics Lab studies methods for understanding life phenomena from the standpoint of biometrics and bioinformatics.
The information obtained by observing and measuring organisms is often unclear and vast, so it is not easy to find biological meaning in it as it is.
The lab develops and uses statistical methods and algorithms, working on approaches for obtaining new insights and interpretations from such information.
Because the data and methods it handles are so diverse, research themes vary from member to member.
Key terms
- Bioinformatics
- The study of analyzing vast amounts of biological information, such as genomes, using computers and methods from information science
- Quantitative genetics
- The study of using statistics to investigate how continuously varying traits, such as plant height and yield, are determined by genetics and environment
- Phenotype
- The observable or measurable characteristics of an organism, such as its shape, size, and yield
NewsLab news
View More ↗ResearchResearch themes
From the standpoint of biometrics and bioinformatics, the lab develops and uses statistical methods and algorithms to provide perspectives for representing diverse life phenomena. It conducts research that draws out "knowledge" for improving agricultural productivity from data such as crop genomes, cultivation environments, and images.
*Illustrative imageDrawing Knowledge from Large Volumes of Crop Data
The lab conducts methodological and empirical research to draw out "knowledge" for improving agricultural productivity from large volumes of crop-related information, such as genomes, gene expression, cultivation environment data, and image data.
*Illustrative imageStatistical Models Linking Phenotypes and Genomes
From the perspective of quantitative genetics, the lab carries out statistical modeling that links variation in observed phenotype data to omics information, including genotypes. It also works on digital phenotyping using images and sensor data.
*Illustrative imageMaking Breeding More Efficient with Data
The lab aims to realize data-driven breeding, which makes plant breeding more efficient by using genomic and phenotypic information. It has worked on acquiring phenotype data with drones and on devising breeding strategies, based on genomic information, for developing new varieties.
MembersFaculty
The members of the Biometrics Lab consist of faculty members, a project assistant professor, project researchers, administrative assistants, academic specialist staff, doctoral, master's, and undergraduate students, and research students.As of 2026
- ProfessorHiroyoshi IwataPublications ↗
- Associate ProfessorGota MorotaPublications ↗
- Assistant ProfessorKengo SakuraiPublications ↗
- Project Assistant ProfessorTanzila RaihanPublications ↗
VoicesStudent voices
Compiled from answers by students who were in the lab. Ratings and reviews reflect individual students' experiences, not the lab's official views.
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Insect Genetics LabFaculty of Agriculture, Major in Agricultural BiologyBasic research mainly on the silkworm; breeding of silkworms…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: “Technology Contributing to Agriculture” Ahman10 / CC BY 3.0 (cropped)
- Drawing Knowledge from Large Volumes of Crop Data: “Residuals for Linear Regression Fit” Thomas.haslwanter / CC BY-SA 3.0 (cropped)
- Statistical Models Linking Phenotypes and Genomes: “Multicolor soybeans in Hale Township” Nyttend / Public domain (cropped)
- Making Breeding More Efficient with Data: “NFDI4BIOIMAGE Calendar June 2025” Warstat, Kevin (ORCID: ) / CC BY 4.0 (cropped)
- Related lab (生産生態学研究室／フィールドインフォマティクス（大森研）
): “Rice Japonica Koshihikari” Siriusplot / CC BY-SA 3.0 (cropped) - Related lab (育種学研究室): “Fukuoka-Tsuzura Rice Terrace in an Early Summer-xl” うきは
市 / CC BY 4.0 (cropped) - Related lab (植物資源ゲノミクス研究室): “Mahangu (pearl millet) field flourishing in the perfect climate in the rural north of Namibia” Shikoha Tautiko / CC BY-SA 4.0 (cropped)
- Related lab (昆虫遺伝研究室): “Bombyx mori 4520” Amada44 / CC BY-SA 3.0 (cropped)
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