A Keyword Recommendation System for GenBank
Yasuhiko Kitamura 1

Tetsuro Nanbu 1

kitamura@info.eng.osaka-cu.ac.jp

tetsuro@kdel.info.eng.osaka-cu.ac.jp

Shoji Tatsumi 1

tatsumi@info.eng.osaka-cu.ac.jp
1

1

Department of Information and Communication Engineering, Osaka City University,
3-3-138 Sugimoto, Sumiyoshi-ku, Osaka 558-8585, Japan.

Introduction

With the progress of Human Genome Project, a huge amount of genomic data is stored in various
databases and is open to the public through Internet. The size of these databases grows rapidly and,for example, the size of GenBank1 , which is a well-known DNA sequence database, reaches more than
5 million entries. However, as the size of database grows, it becomes more diﬃcult for users to retrieve
necessary data. Many of genome databases consist of full text data and the keyword search method is
widely used for their retrieval. Hence, when a user submits a simple query with a general keyword, hereceives a large number of search results and is obliged to add another keywords to reduce the numberof results.
In this paper, we propose a keyword recommendation system[1, 2] that recommends proper keywords to the user and show a prototype where the technique is applied for GenBank. Advantages ofour system are as follows.
• It assists users who have diﬃculty to think of proper keywords to narrow down the search.
• It may lead to creative thinking support for researchers by showing keywords related to their
original inputs.

2Method

To recommend proper keywords, we use keyword pairs of co-occurrence as the candidates. A keyword
pair of co-occurrence is a pair of keywords that appear in an identical entry. For example, in “mouseliver milia Mus musculus cDNA clone,” “mouse” and “cDNA” are a keyword pair of co-occurrence.
Then, for “mouse” as an original input, “cDNA” can be a keyword candidate for recommendation.
We sort co-occurred keywords according to the frequency.
In addition, we can use thesaurus and log data to sort the keyword more elaborately. Thesaurus
is a kind of dictionary that contains biological terms and can be used as a measure that shows thesigniﬁcance of keywords in general sense. Log data is a record of input keywords and can be used asa measure that shows keyword preference of a user or a group of users.

3Prototype

We developed a prototype for GenBank2 as shown in Fig. 1. For testing, we use only 80,000 entries ofGenBank at this moment. At ﬁrst, we start to use this system by giving one or more query keywords
12

http://www.genome.ad.jp/dbget-bin/www bfind?genbank-today
http://www.kdel.info.eng.osaka-cu.ac.jp/ tetsuro/

Figure 1: GenBank Keyword Recommendation System.
as usual in the left frame. By clicking “Submit,” the systems returns recommended keywords, links todata entries, and other statistics in the right frame. By clicking a recommended keyword in the box,
the system automatically adds it to the query keywords in the left frame. We can change the weightof thesaurus and log data by specifying it in the parameter boxes.

Acknowledgments
We thank Minoru Kanehisa, Susumi Goto, Harumi Murakami, and Hiroyuki Kawano for their helpfulcomments and supports. This work is partly supported by a Grant-in-Aid for Scientiﬁc Research onPriority Areas, “Genome Science,” from the Ministry of Education, Science, Sports and Culture inJapan.

References[1] Balabanovic, M. and Shoham, Y., Fab: Content-based, collaborative recommendation, Communications of the ACM, 40(3):66-72, 1997.
[2] Kawano, H., Mondou: Web search engine with textual data mining, Proc. IEEE Pacific Rim
Conference on Communications, Computers, and Signal Processing, 402-405, 1997.