Quantitative biology in our laboratory refers to "the search for quantitative laws and principles that define life through quantitative descriptions of living phenomena. At the same time, we believe that the field of quantitative biology is generally defined as a collection of experimental, measurement, data analysis, and modeling techniques that are necessary for quantitative analysis of the living phenomena. Quantitative biology itself may not necessarily require big problems such as the principles of life. If we can do something interesting and useful by using effective tools for quantitative analysis, that is what quantitative biology is all about. In our laboratory, the projects of "quantitative cell biology," "quantitative immunology," and "quantitative embryology" fall into this category.
Quantitative biology is like a brother to systems biology, which aims to understand living phenomena as systems. However, quantitative biology is more concerned with the means and methods of understanding life on a quantitative level than with the philosophy. Researchers in two fields are greatlly overlaping.
Generally speaking, theoretical biologi is defined as the field of applying mathematical theories to living phenomena. One of its origins lies in ecology and evolution where experimental verification and reproduction are much harder than those in physics and chemistry. Mathematics plays an extremely important role as a substitute for natural language in order to increase the rigor and objectivity of the discussion. Another origin is from population dynamics (demography and epidemiology) and physiology in which we need mathematics to describe and predict phenomena in a more quantitative manner. However, owing to technological advancements of quantitative analysis, some problems of evolution and ecology can now be reproduced and quantitatively verified at least at the cellular level. Biological diversity can also be quantitatively and intensively measured using next-generation sequencers. With the support of new quantitative data and the knowledge gained from it, theoretical biology is becoming a field closer to theoretical physics by incorporating biochemical theory and other ones. We thank that major questions there would be the characteristics that distinguish living systems from non-living ones, the principles of evolutionary adaptation, and the mechanisms of diversity formation and maintenance.
Life is a class of physical phenomena. We believe that "living state" is one that is inherently rare in the physical world but majorized and maintained by self-replication and selection. In a non-equilibrium state, the flux of energy and matter keeps the system out of equilibrium. In the living state, self-replication and selection act as driving forces to maintain the state.
We believe that understanding the typical behavior of the physically rare "living state" is the key to understanding life. For this purpose, we believe that it is necessary to develop a unified theory to describe the relationship between the non-equilibrium state inherent in the cell, the smallest unit of life, and the selection that acts on self-replicating populations.
We believe so, and we are working on achieving it. In the first place, pursuing theory is the activity to search for a better description of phenomena and the world. We believe that "seeking a description that goes beyond mere facts and observations" is in itself making a theory.
The quality of a description depends on how faithfully it describes and predicts the phenomenon. If we pursue a quantitative description of living phenomena, then the theory that describes it must also be quantitative. Mathematics is an indispensable tool for this purpose. In addition, mathematics allows us to discover unexpected relationships between various things. The interrelationships between fitness, information, and entropy, for example, are supported by mathematical results. They are not just a concept described in natural language.
This is because we believe that the quantity of information, in addition to the usual thermodynamic quantity, is essential to define the typical behavior of the "living state. Information plays an important role in non-equilibrium systems, but it plays an even greater role in living systems, where self-reproduction and maintenance by selection are assumed.
From information thermodynamics, we know that information and entropy are interchangeable quantities. On the other hand, our research has shown that information and fitness (selection pressure) are interchangeable. In addition, self-replication accompanies some thermodynamic cost. Information plays a role in connecting fitness with thermodynamic quantities.
Bioinformatics attempts to discover knowledge and laws from biological data by using mathematical and information techniques. Theorical biology is mainly concerned with the mathematical formulation of concepts that constitute living phenomena, and their verification and generalization.
Theoretical and informatic research requires no special devices or equipment. There are no physical or financial obstacles. You can start it right now. A wide variety of information, including textbooks, research papers, and public data, is readily available if you are affiliated with a university or other research institution. If you have the passion, all you have to do is move your hands. You can start by following the results of your textbook or paper. If there is a problem that you cannot solve by yourself, we welcome discussion.
From 2009. Prof. Kobayashi has started it after moving from Kobe, Riken. The name of lab has been Laboratory for Quantitative Biology since then.
They are from applied math, physics, bioinformatics, engineering, neuroscience, and biophysics.
We have huge whitebords and projectors. You can access a couple of local servers and CPU/GPU supercomputers provided by UTokyo. No experimental equipment.
From Grants-in-Aid for Scientific Research by the Japan Society for the Promotion of Science (JSPS), we have obtained DC, PD, New Academic Fields, Young Scientist A, Budding Researchers, Basic Research B. From JST, we have PRESTO, CREST, etc. More detail can be found on 日本の研究.com.
The Institute for Quantitative Life Sciences (IQB) looks similar to our lab, but they are totally independent.
We accept graduate students from Department of Mathematical Informatics (MI) at Grad. school of Information Science and Technologiy or from Department of Electorical Engineering and Information Systems (EEIS) at Grad. school of Engineering, UTokyo. You can check the past exams and other information from HPs of the departments. You are strongly encouraged to visit our lab before application. There is chemistry between a laboratory and a student.
You are expected to have the knowledge of mathematics or physics at the undergraduete level and the training and experience of scientific programming. While it is important to have an interest in biology, knowledge of biology is not necessarily a prerequisite.
You are supposed to know basic math (linear algebra, calculus, functional analysis, and statistics). You must learn one of the scientific programming languages, e.g., Python, C, or Matlab such that you can use it basically without any assistance. You are also encourged to study either basic physics (mechanics, analytical mechanicsm, thermodynamics and statistical physics) or informatics (bioinformatics, machine learning)
No core time except the lab meeting. You are supposed to manage yourself to do your research and study. Lab provides the place and the opportutity to discuss about what you did.
We have lab meeting every week. We also have more focused project meetings every month on average.
You may present at the lab meeting every two months on average. Also grad students have to do another presentation as a part of lecture.
For 3rd and 4th year undergraduates, I give a lecture "Theoretical Biology" in S1 term at the Faculty of Science and two talks at a lecture on "Introduction to Brain Science" in A semester. Every other summer, I have a lectore on "Special Lecture on Mathematical Informatics IV" for grad students at the Department of Mathematical Informatics.
In general, you can choose one from the themes of the projects we are working on. The topics can be broadly divided into theory and data analysis. If you have an theme that you would like to work on and also if you have sufficient ability to manage yourself, we also recommend that you pursue your own theme.
Our lab has a strong atmosphere of theoretical physics. We are flat and exchange comments and questions without any reserve. You should be able to distinguish them from personality attack. You are also expected to be autonomous on your research project.
The topics coved by the exam of MI and that of EEIS differ a lot. Please select the best grad. school based on your bacground. Any exam is partially ruled by chance. Also some topics picked in the exams may not be overed in other depertments or universities. You should be prepared. If you need, you can consult us.
Master graduates got jobs at Mitsubishi Research Institute, Toyota Motor Corporation, Chubu Electric Power Company, Yamaha Motor Corporation, Bank of Japan, Yahoo Japan, venture businesses, prefectural government officials, NTT East, and Softbank. Doctor graduents or posdocs found jobs as project assosiate prof., regular assistant prof., tenure-tracked asistant prof., research assosite for National Research Institute of Police Science, JSPS PD and others.
Noting particular as lab. But the grad schools provide RA, schalorship, and others. Doctor students are strongly encouraged to take the JSPS Fellowship for Young Scientists (JSPS DC).
We support your travel expense to present at a workshop or conference depending on the level of your research results (and the Lab's budget at the time) Some master studends were supported to have presentations in international conferences held outside of Japan.
We have welcome parties, get-togethers, and farewell parties (about four times a year in total). We also organize a big BBQ party in May or June every year (however, all parties are cancelled during Corona).