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Research

Shigeto Seno

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Shigeto Seno

Bioinformatic Engineering Genome Information Engineering Associate Professor

Please tell us about your research.

My research is in a field called bioinformatics. Bioinformatics is a field with the goal of developing new things, such as methods and algorithms used to analyze life science data using information science techniques. In particular, I am focusing on gene expression analysis, which is a method to analyze the expression levels of genes. Gene expression levels are table data, like data you would open as a spreadsheet, written in very large rows and columns. It is similar to table data where each gene is lined up in the rows and many samples are lined up in the columns. The research is to analyze similar patterns in such table data, or to analyze which factors should be paid attention to.

At the same time, I am also working on cell image processing. The purpose of this research is to analyze images of cells taken with a microscope. Cell image data can tell us a lot when we look at it, but in order to analyze it by computer, we need to extract "variables". In the case of gene expression analysis, which I already mentioned, it is possible to analyze the data in rows and columns in the form of a spreadsheet from the beginning, but in the case of images, the starting point is to think about the expression of various features from what kind of image this is. Once the features are extracted, the process is similar for both cell image processing and gene expression analysis. In other words, the analysis is based on how to find similarities and separate differences.

Can you tell us about how you decided to study this field?

For many students, their first motive to start research is choosing a laboratory when they are in their fourth year of university. I was in my senior year during the years 1999-2000. It was the dawn of genomics, just after the human genome was elucidated, and genomics was attracting attention worldwide.

I have always been a fan of science fiction, and I think genomes were often used as a subject in science fiction at that time. There were many novels, movies, and games based on the genome, such as "Parasite Eve."
Another thing that marked the time was IT. I entered university in 1997, so I was in high school when computers started to become popular, such as with Windows 95 being released. At that time, I thought that if I was going to study at university, it would be IT, and if I was going to do research, it would be IT + genomics. With this background, I entered the Seminar of Genome Information Engineering.

When I was assigned to the Seminar of Genome Information Engineering in the Matsuda Lab as a fourth-year undergraduate student, gene expression analysis was just beginning to appear as a research topic. So, the first research I started as a student was expression analysis. You may be familiar with the kind of image analysis called "heat map", which has a clustering tree structure on the top and side of the image which can be rearranged and organized at will. It was the first time that such an analysis and visualization method was used with microarrays. I thought that the Eisen plot, with its beautiful red and green patterns, was beautiful, and that was one of the reasons I started my research. From there, I continued to research clustering of expression profiling during six years (B4 to D3) as a student at Matsuda Lab.

At that time, I had no idea that I would make this my lifelong research. However, I would like to ask the students - do you ever feel that there are still too many things you don't understand about what you studied at university, even though you are studying the most advanced things? When you think things like, "After graduating, it's just work," "No more studying and research," you may still feel like there is so much left that you don't understand. That's how it was for me when I was a master's student. I studied hard at university and learned more, but there were too many things I didn't understand. Above all, I thought that once I started working, I would remain clueless about it. So, I went on to become a doctor, and by a stroke of luck, I am continuing my research at the Matsuda Lab.

When did you start your research on image analysis?

It was about 10 years ago that I was approached by Dr. Matsuda to do research on image analysis after I had exchanged ideas with a professor from the School of Medicine at a seminar. It was a time when research on expression analysis was at a standstill, and I felt that image analysis would be interesting, so I decided to start studying it as it was a new field. Nowadays, image-related research is very stimulating because there are various research subjects such as deep learning, all of which are being studied in depth. However, because of this, there are so many people researching it, so it's hard to make up my mind to specialize in image analysis and work hard at it alone. I am working on it in a shallow and broad way, leaving an escape route.

You have been doing research for a very long time. What gives you motivation?

Basically, I am not a very motivated person, and I think I am the type of person who does more research when there is pressure from others. Therefore, I am involved in quite a lot of collaborative research. I am able to work regardless of my motivation, and I am able to help people in other fields with their analysis, and I am also able to refresh myself by interacting with them. I am sorry that I take on so many projects that my response tends to be slow.

Our joint research mainly involves analysis of projects brought to us by professors in other departments. Recently, I have been working with a professor at the Emergency Center of Osaka University on RNA expression analysis related to COVID, and on omics analysis, which is the analysis of expression data, protein data, and microRNA data together. I am also working with professors at Kyoto University on expression analysis in relation to fat and foods such as soybeans and tomatoes. With the help of my master's students, I am currently working with a professor from the Department of Pharmaceutical Sciences on image analysis of muscle recovery, and with a professor from the National Institute of Information and Communications Technology on automatic recognition of microorganisms from a microscope that shows many of them. I'm also working with a breast surgeon to develop a system to check whether cancerous tissue is removed in its entirety during surgery. At any given time, I am working on about 10 to 20 joint research projects at the same time. I am sorry that the progress of my research tends to be uneven, but there are times when the knowledge gained from one research might be a hint for another one.

There are many good professors who are associated with Osaka University. They have faith in their own research, and they teach me a lot through their research. As I get older, the people who teach me become more and more valuable, and in that sense, universities are interesting. I think it is an environment where there are many specialists that can teach you various things you don't know.

If I were to ask you how your research has been connected to society, what would you say? How far does your research have to go before it becomes a goal?

If asked in such a straightforward manner, it becomes difficult to answer. Even when I think of new analysis methods in terms of information science, I sometimes end up thinking that the old-fashioned logistic regression is good enough. In fact, the methods developed 30 or 40 years ago are about 90% accurate. In such a situation, for me, doing joint research and being useful to researchers in other fields and companies is an easy way to connect with society. And I will do what I want to do, as my own research. Because I feel that if I don't enjoy it, it is difficult to explain the joy of research to students.

It's hard to decide on a goal for your research. For me, the reason I wanted to do information was because of artificial intelligence and automation. So, in the end, I would like to secretly create a system that can automatically do the kind of analysis that I am asked to do in collaborative research, and gets it done while I'm sleeping.

When you get stuck in your research, do you have any ways to refresh or get through it?

It's like doing another collaborative research project to refresh your research. Even though many things are going wrong, I feel better when there is one thing that is going well. I try my best not to get stressed out.

As for how to refresh myself when I get stuck in my research, I was unable to do so when I was a student. When I was a student, I couldn't do that. I came to school to study and gain knowledge, but I couldn't decide on my own research theme before I even knew the full scope of the field. It's really difficult to decide what to research when you are just starting your studies. It's also really hard for students to change their research theme after they have decided on it, because they can't do it by themselves. You have to deal with the work you have to do even though you can't do it.

So, on the other hand, I think the main thing is to find out what you want to do. Do the research you want to do. Find the problem that you really want to solve and solve it, rather than the data you receive. Do it as if you are not being forced to do it. If you do this, you can bypass a dead-end situation. You become able to decide on the theme on your own, and thus able to bypass a dead-end, so I think that's important. . It's a lot of work, though.

Also, you may also hear this a lot, but I think it is important to take care of social connections outside of the laboratory. Especially nowadays, with the COVID-19 epidemic, students tend to lose communication with each other, making it difficult for them to talk and relieve stress, so I want you to take care of social connections outside of your lab.

As you will find out as you continue your research, research basically does not go well. It is important to reduce stress, but the basic premise is that you need to spend a certain amount of time to do it. So, the most important thing is to go to bed early and get up early properly. Get up in the morning, do your research, and sleep properly at night. For example, I think there are very few university students who study from 9:00 a.m. to 5:00 p.m., the same amount of time they spent studying in junior high and high school, so various results will start to show if you do that much.

Do you have a message for students who are planning to enroll in the graduate course?

The good thing about our laboratory is that we have a variety of research themes, whether you are interested in biotechnology or information systems. The field is quite wide. In addition, not only in bioinformatics, but also in any other field of work, there are many things that you need to study in addition to information science, your own field of specialization. For example, you need to have detailed knowledge about the products you are going to make, or about law and business. For most of the students in the Department of Information Science, biology is also an unknown field. They don't understand it at all. Therefore, I believe you will acquire the attitude of studying what you don't understand with a premise that you don't understand it, and I think that is very useful for everyone. I think it would be interesting to have many different people come.

I think it is more important for students to enjoy their research than to produce good results, so I recommend that they try various things. The most important thing is to enjoy research, but if there are other things you enjoy besides research, I hope you can take advantage of your position as a graduate student, the good environment, and the ample time. However, if you are doing well in your research, your student life will be more enjoyable. I think it is the same as with sports, music, or anything else - research is more fun when you gain a certain amount of skill. I want to tell students that studying and doing research is fun.

From a student

I The first characteristic of this laboratory is that it is free, and you can do what you want. This is what I focused on when I chose my laboratory, and I have felt it since I joined. When I go to ask a question, they are waiting for me, and when I ask, they help me. There is no pressure to do research, so I can focus on what I want to do while I am a student. If you want to concentrate on your research, they will help you do so, and I think that kind of balance is one of the things that's good about it.

W I often feel that the lab provides guidance tailored to each individual student, and supports them while learning about their personalities. I feel that no matter what kind of student joins, they will be able to provide support that fits the student's needs. For me, I felt that from the beginning, and I am grateful because of it. I would be happy if more female students would join as well. Because there are only a few female students, it may feel kind of small, but I have never had any problems in my student life and I don't mind it.

*Masks were removed only during filming.