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Mathematical Bioinformatics Lab
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A lab that uses mathematics to uncover life phenomena, from cells to the brain to human society.
AboutAbout the lab
Uncovering complex life phenomena through mathematics.
The Mathematical Bioinformatics Lab conducts research that elucidates complex life phenomena using mathematical tools such as nonlinear dynamics, stochastic processes, and information theory.
Its subjects span multiple levels, from cells to the brain and on to human society.
Each faculty member covers a broad range of topics in the life sciences, medicine, and human and social sciences where mathematics plays a role.
The lab aims to apply the knowledge it gains to medicine and engineering.
Key terms
- Nonlinear dynamics
- The mathematics of how phenomena change over time when cause and effect are not proportional. Small differences can lead to large differences in outcomes
- Stochastic process
- A mathematical framework that uses probability to describe phenomena that change over time while being influenced by chance
- Information theory
- A theory that uses mathematics to deal with the amount of information, and with the efficiency and errors involved in transmitting it
ResearchResearch themes
The lab studies life phenomena at levels ranging from cells to the brain to human society, working to elucidate their operating principles and information processing mechanisms, and to predict and control their behavior. It aims to build new mathematical analysis methods and universal theories for understanding and making use of complex biological systems.
*Illustrative imageTheoretical Neuroscience
Explores the principles by which the brain processes information, and how these are realized in the bodies of living organisms.
*Illustrative imageTheoretical Biology
Uncovers the laws governing complex life phenomena, from cells to evolution, development, and immunity, from a mathematical perspective.
*Illustrative imageBiological Information Processing
Information processing is a property unique to living systems. The lab aims to understand the basic principles of the information processing carried out by living things.
*Illustrative imageBrain-Inspired Information Processing
Considers how to build information processing that works like the brain. Learning from the brain, the lab lays the foundation for designing such systems.
MembersFaculty
- ProfessorTakashi KohnoPublications ↗
- ProfessorTetsuya J KobayashiPublications ↗
- Associate ProfessorKantaro FujiwaraPublications ↗
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: “Mouse Embryo Cerebellum ( )” NIH Image Gallery from Bethesda, Maryland, USA / Public domain (cropped)
- Theoretical Neuroscience: “Нейрон коры с множеством дендритных шипиков” Sergb95 / CC BY-SA 4.0 (cropped)
- Theoretical Biology: “Healthy Human T Cell” NIAID/NIH / Public domain (cropped)
- Biological Information Processing: “Dictyostelium Late Aggregation 1” Bruno in Columbus / Public domain (cropped)
- Brain-Inspired Information Processing: “Neuromorphic Nanowire Network” DrHughManning / CC BY-SA 4.0 (cropped)
- Related lab (Mathematical Data Science Lab): “Rosenbrock function 2” RokerHRO / Public domain (cropped)
- Related lab (Brain Mathematics and Information Collaboration Lab): “Synapsin and CamK2 positive neurons” ManuelSchottdorf / CC BY-SA 4.0 (cropped)
- Related lab (Systems Pharmacology Lab): “Lab mouse mg 3263” Rama / CC BY-SA 2.0 fr (cropped)
- Related lab (Kobayashi Lab): “Mitotic LLC-PK1 cells, fluorescence microscopy ( )” ZEISS Microscopy from Germany / CC BY 2.0 (cropped)
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