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Seino Lab
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A lab that uses AI to analyze big data in chemistry and search for new materials.
AboutAbout the lab
Accelerating chemistry with data and computation
The Seino Lab researches cheminformatics, analyzing big data in chemistry with artificial intelligence (AI) techniques.
The compounds that arise from combinations of elements are almost infinite in number, and the compounds registered in databases exceed 100 million.
Chemistry has so far relied heavily on the experience and intuition of experimenters, and it was not always possible to arrive at a compound with a targeted property.
By linking experimental chemistry, computational chemistry, and informatics, the lab aims to build a framework for materials development that does not depend on chance discoveries.
Key terms
- Cheminformatics
- A field that handles large amounts of chemical data with methods from information science to predict the properties of substances and how to make them
- Computational chemistry
- A field of chemistry that calculates the behavior of molecules on computers to predict the properties of substances
- Inverse problem
- A problem of tracing back from results to causes. Here, it means searching backward from desired properties to find compounds.
NewsLab news
A master's student won the Excellent Poster Award at the 48th Symposium on Chemoinformatics
A master's student won the Scholarship Award at the Society of Computer Chemistry, Japan 2025 Spring Meeting
A master's student won an Outstanding Poster Presentation Award at the 14th CSJ Chemistry Festa 2024
A paper from the lab was published in the Journal of Computational Chemistry
A master's student won the Yoshiro Sekine Award of the Department of Chemistry and Biochemistry
ResearchResearch themes
In chemistry, combinations of roughly 100 elements give rise to a nearly infinite number of compounds. Computational chemistry has become able to predict the properties of compounds, but the inverse problem of searching backward from desired properties to the compounds that have them remains unsolved.
*Illustrative imageSelecting from a vast number of compounds
The compounds registered in compound databases exceed 100 million and continue to grow year by year. The lab tackles the question of how to select compounds with desired properties from among them, using methods from information science.
*Illustrative imageDesigning new compounds
If compounds not yet known are included, the range of possible compounds expands far further. The lab studies how to design useful compounds from among both unknown and existing ones.
*Illustrative imageDesigning synthesis routes
Even when a promising compound is found, it cannot become a material if it cannot actually be made. The lab works on how to synthesize promising compounds, aiming at a system that automates the design of synthesis routes.
MembersFaculty
The members of the Seino Lab consist of faculty, researchers, and students in the doctoral, master's, and undergraduate programs.As of 2026
- Associate ProfessorJunji Seino
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: “Pentane space filling model 8273” Bin im Garten / CC BY-SA 3.0 (cropped)
- Selecting from a vast number of compounds: “Microtiter plate” Jeffrey M. Vinocur / CC BY 2.5 (cropped)
- Designing new compounds: “Maprotiline ball-and-stick model” Vaccinationist / CC BY-SA 4.0 (cropped)
- Designing synthesis routes: “Equipment and glassware” Belikov Maxim / CC BY 4.0 (cropped)
- Related lab (Sakti研究室): “All-solid lithium-sulfur battery ( )” Oak Ridge National Laboratory / CC BY 2.0 (cropped)
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- Related lab (井村研究室): “Front of 4th century CE Roman Lycurgus Cup, British Museum (1958,1202.1)” Chappsnet / CC BY 4.0 (cropped)
- Related lab (中井研究室): “Benzene IBO” Alicesu / CC BY-SA 4.0 (cropped)
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