Computational Biology Research Center[CBRC]

Advanced Industrial Science and Technology[AIST]
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Voice of a Researcher

Hear from our researchers about the type of research activities they participate in, and reasons why they work at the Computational Biology Research Center.

Paul Horton Paul Horton
Leader, Sequence Analysis Team
Born in Kennewick, Washington (USA), 1966.
UC Berkeley, Computer Science (1997)
I joined the CBRC after living in Taiwan for some time.
จก When did you start at the CBRC? What brought you to this center?

I developed an interest in East Asia and its languages early on. For my master's degree I was fortunate enough to have a chance to join a prominent bioinformatics group in Kyoto. After three years there, I went back to the US to do my PhD at UC Berkeley. Following that I worked for Dr. Akiyama from 1998 to 2000 in Tsukuba. That was one of the connections that eventually lead me to the CBRC.

I spent much of the two years starting in 2001 in Taiwan, a country in which I have a special interest, working as an software engineer for a local company. After leaving Taiwan I looked into the opportunities available at the CBRC and ended up in my current position.

Our team has new and continuing research projects.
จก Can you tell us about your current research topics?

Very broadly my research can be divided into two areas. An area which I am investigating with several other past and present team members is gene expression regulation. We are developing methods to predict gene expression regulatory elements in genome sequences based on sequence patterns. Measured expression data is then feedback to this process to improve the prediction accuracy.

Another topic is protein subcellular localization prediction. I have worked on this topic for several years -- so it is a relatively old one. However it is fairly well known and has good number of users.

Productive research requires finding a balance between new and more mature topics. If only the newest topics are exclusively pursued it is difficult to maintain and extend past accomplishments.

Now is a good time for quick collaborations, as opposed to deep reflection.
จก What are the advantages to doing research at the CBRC?

Research can be pursued in two ways. One approach is to isolate yourself to concentrate on gaining a deep understanding of a problem. This is the approach which I took while working as a research in Tsukuba. Another approach is to focus on breadth by gathering knowledge from multiple researchers and data sources. This approach can be very successful. At the CBRC, it is possible to adopt the first approach, but the number of top researchers with various backgrounds makes the CBRC an excellent place to pursue the second approach. Indeed my research style at the CBRC is closer to the quick and broad approach.

Now is an important time for the integration and analysis of biological data.
จก Can you tell me more about the quick and broad approach?

We know in an exciting time in which all kinds are biological data are available, often publicly. The question is how to integrate and analyze the wealth of data from disparate sources. A good strategy to address this is to work in teams -- letting each researcher contribute his strength as necessary.

The CBRC has sufficient computing power and research expertise for quick and effective analysis. For example, the CBRC researchers have done excellent work in the field of protein structure prediction and genomic sequence analysis. By working with these experts, research in related fields can be done quickly and effectively. I think the most attractive aspect of the CBRC is the opportunities to pursue collaborative research.

Studying the fundamentals is important.
จก Do you have any comments for researchers or students who want to participate in the CBRC in the future?

For students I would say to make sure to get a solid grounding in the fundamentals. Once you start work for a research institute it is difficult to make time for studying the basics. But basic knowledge is invaluable in performing research. So I would suggest choosing one field in particular (biology, applied mathematics, computer science, etc.) and learn the basics of that topic very thoroughly. For example, I would suggest fundamental topics such as algorithms or graph theory before studying AJAX.

I believe bioinformatics will continue to be a very promising field. In particular, the medical applications of bioinformatics and bioinformatics supported research are expected to be revolutionary. By pooling the abilities of several top researchers from various areas I believe bioinformatics will be even more successful in the future.

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